Latest Open Tech From Seeed

【Exciting 2024 Kickoff Offer🤩】Up to 99 Pcs! Enjoy FREE Assembly for Your First PCBA Order!

Jiayu.Yang — Thu, 25 Jan 2024 03:02:15 +0000

We’re thrilled to kick off the year with a special offer: Get FREE assembly (up to 99 pcs for one order) on your first PCBA order placed in 2024. Whether you’re a new or returning customer, this exclusive deal is yours to seize!
Duration: January 25, 2024 (12:00 PM GMT+8) to February 25, 2024 (12:00 AM GMT+8)
Note: This offer still applies to users who placed PCBA order(s) before January 25!

Place your order now and experience hassle-free assembly on us!

Why miss out on this fantastic opportunity? Elevate your projects without worrying about assembly fees. Take advantage of this limited-time offer and experience seamless PCB assembly without the extra cost.

Scale up Your Creation With Seeed Studio Fusion

Seeed Studio Fusion serves as the comprehensive service platform for Seeed Studio, a global one-stop online platform offering PCB manufacturing, PCB assembly and hardware customization with global sourcing capability. Whether you need prototyping, mass production, custom solutions for open-source products, or the transformation of your creative ideas into profitable products, Seeed Studio Fusion can meet your requirements.

The post 【Exciting 2024 Kickoff Offer🤩】Up to 99 Pcs! Enjoy FREE Assembly for Your First PCBA Order! appeared first on Latest Open Tech From Seeed.

Seeed Studio Accelerates Vision AI and Generative AI at the Industrial Edge with NVIDIA

Elaine Wu — Tue, 23 Jan 2024 18:00:00 +0000

[Shenzhen, China] —January 23, 2024— Seeed Studio, an Elite partner of the NVIDIA Partner Network, today announced it is bringing NVIDIA Metropolis Microservices on Jetson to their reThings hardware platform, powered by NVIDIA Jetson Orin. The collaboration offers a modern, microservices-based software stack to streamline workflows for developing vision AI and generative AI applications — from AI creation and building inference pipelines to scalable deployment. As a pioneering embedded AI partner to global developers, Seeed offers hardware services for the NVIDIA Jetson edge AI and robotics platform, from prototyping to solution development.

NVIDIA Metropolis Microservices for Jetson helps developers modernize their app stack, streamline development and deployment, and future-proof their apps, delivering the ability to bring the latest generative AI capabilities to any customer through simple API calls. Its application microservices include video storage and management, pre-built vision AI inference pipelines, system monitoring, and cloud connectivity. Its platform microservices include system monitoring, IoT gateways, and cloud connectivity services to help with solution maintenance. And its powerful reference workflows help developers get started immediately.

“The modular and extensible architecture of NVIDIA Metropolis Microservices will help provide faster solutions to market across an ever-growing Al application portfolio,” says Leslie Liao, VP of Edge Computing at Seeed Studio. “Our collaboration with NVIDIA will help our work delivering the power of modern AI at the edge, integrated with real-world data from AIoT sensors.”

Generative AI transforms vision AI by creating synthetic visual content for dynamic applications like simulations and AI model training. This shift from analysis to creation enhances system capabilities. NVIDIA Jetson AGX Orin and Orin NX systems deliver up to 275 TOPS of AI performance, enabling the running of large language models and vision transformers locally. To facilitate the integration of generative AI applications into Metropolis Microservices-based systems, NVIDIA offers a collection of Python modules that developers can leverage.

The Seeed Studio reThings Series, powered by NVIDIA Jetson, offers edge devices in various form factors. These devices are designed for power efficiency, high AI performance, and hybrid connectivity, and feature an excellent cooling design for scalable production deployment. Fully compatible with NVIDIA’s software stack, these advanced embedded AI systems offer fast, next-generation AI product development across industries – from smart cities, security, and industrial automation to smart factories – and are ideal for advanced robotics applications across these sectors.

CVEDIA is a cutting-edge technology firm that specializes in the development, deployment, and integration of intelligent video analytics solutions that support all NVIDIA Jetson platforms. Leveraging its computer vision expertise and proprietary synthetic data technology, CVEDIA will offer a range of reliable and cost-efficient AI-powered video analytics solutions on Seeed’s reThings edge devices and will be offered through NVIDIA’s Metropolis Microservices on the Jetson platform. This collaboration will accelerate the adoption and implementation of vision AI across all AIoT cameras.

To manage the applications and devices securely, Allxon, a preferred third-party fleet management partner for NVIDIA, took early steps in integrating the Video Storage Toolkit into its Allxon Plugin Station. Allxon’s Fleet Provisioning ensures the efficient deployment of thousands of edge AI devices and seamless BSP OTA Updates for Jetson. Today, Allxon also announced it is combining powerful fleet management with modern AI software stacks and development workflows through NVIDIA Metropolis Microservices for Jetson.

Leveraging NVIDIA Metropolis Microservices, Seeed Studio is looking forward to collaborating with global developers and leading AI software companies to develop cutting-edge, future-proof applications. In 2024, Seeed plans to expand its Jetson Orin-powered reThings hardware solution tailored to meet the unique hardware needs of different industrial environments, with a focus on integrating vision AI and generative AI into various industry deployments.

Seeed NVIDIA Jetson Ecosystem

Seeed is an Elite partner for edge AI in the NVIDIA Partner Network. Explore more carrier boards, full system devices, customization services, use cases, and developer tools on Seeed’s NVIDIA Jetson ecosystem page.

Join the forefront of AI innovation with us! Harness the power of cutting-edge hardware and technology to revolutionize the deployment of machine learning in the real world across industries. Be a part of our mission to provide developers and enterprises with the best ML solutions available. Check out our success case study catalog to discover more edge AI possibilities!

Take the first step and send us an email at edgeai@seeed.cc to become a part of this exciting journey!

Download our latest Jetson product Catalog to find one option that suits you well. If you can’t find the off-the-shelf Jetson hardware solution for your needs, please check out our customization services, and submit a new product inquiry to us at odm@seeed.cc for evaluation

The post Seeed Studio Accelerates Vision AI and Generative AI at the Industrial Edge with NVIDIA appeared first on Latest Open Tech From Seeed.

4 Most Promising LPWAN Connectivity: A Comprehensive Comparison of LoRaWAN, Amazon Sidewalk, Helium, and Cat-M,

Lily — Mon, 22 Jan 2024 14:30:00 +0000

The Internet of Things (IoT) is revolutionizing our world, enhancing decision-making processes, operational efficiency, and cost-effectiveness by integrating smart devices to collect, analyze, and act upon data. Central to this digital transformation is IoT connectivity, a critical factor that dictates the seamless transmission of data across various layers of IoT infrastructure.

Navigating the intricate world of IoT connectivity can be daunting. With a plethora of options ranging from Wi-Fi and Bluetooth to advanced cellular technologies like NB-IoT and Cat-M1, not to mention solutions such as LoRaWAN and RPMA, selecting the ideal connectivity for your IoT project requires a deep dive into the capabilities and advantages each offers.

Source: ide.eu

Enter LPWAN (Low Power Wide Area Network), a term that encapsulates a diverse spectrum of connectivity options. LPWAN is not merely a single standard but an umbrella term for a variety of implementations—some proprietary (eg. Sigfox), others open-source—united by their common traits of low power usage and extensive coverage areas. LPWAN stands out for its exceptional attributes, providing cost-effective, low-power solutions that are instrumental for a myriad of IoT applications.

In this blog post, we’re shedding the spotlight on four of the most promising and rapidly emerging LPWAN technologies that are shaping the future of IoT: LoRaWAN, Amazon Sidewalk, Helium, and Cat-M. Here’s what we’ll cover:

By the end of this post, you’ll have a clear picture of the LPWAN landscape, equipped with the knowledge to select the most suitable LPWAN connectivity for your IoT applications. Now, let’s explore these powerful LPWAN technologies that are connecting our world in unprecedented ways.

What is LPWAN?

LPWAN, or Low-Power Wide-Area Network, is a collection of various types of wireless telecommunication designed for sending small data packets (typically 10 to 10k bytes) over long distances (usually several kilometers), all the while maintaining low power consumption. It’s a game-changer for industries like agriculture, smart city development, efficient workplace management, precise asset tracking, and sensitive environmental monitoring. In these fields, devices often need to transmit minimal data across expansive distances without the need for frequent battery replacements.

Source: emnify.com

Unlike smartphones and other consumer devices that demand high-speed, high-bandwidth connectivity, IoT devices thrive on lean data exchanges. They don’t need the constant, high-speed data streams that we, as consumers, have come to expect. Instead, these devices perform optimally with intermittent transfers of small data packets, a method that drastically cuts down on power usage.

LPWAN technologies have a few key characteristics that account for their rising popularity, as highlighted in The Market Insights report, which states, “The LPWAN market size exceeded USD 5 billion in 2022, and it’s projected to expand with a robust 50% CAGR from 2023 to 2032.” This growth is fueled by the escalating demand for IoT and embedded devices, prompting telecom operators to invest in the commercialization of these networks.

The core attributes that make LPWAN connectivity appealing are:
●Low Power Usage: LPWANs are engineered to ensure devices have low power consumption and an extended battery life.
●Wide Area Coverage: These networks can transmit data over considerable distances, often surpassing traditional wireless networks with a range of tens of kilometers.
●Cost-Efficiency: The streamlined protocols and reduced hardware complexity inherent in LPWANs help lower device costs. The far-reaching coverage, coupled with a straightforward star network topology, minimizes the need for pricey infrastructure.

LPWAN is a catch-all term that includes a variety of technologies, each with unique implementations and protocols. Here’s a rundown of some prevalent LPWAN connectivity options:
●LoRaWAN
●Helium
●Amazon Sidewalk
●Sigfox
●Narrowband-IoT (NB-IoT)
●LTE CAT-M1
●MIoTy
●Random phase multiple access (RPMA)
●Weightless

Each of these LPWAN technologies has distinct features and optimal use cases. As a leading IoT hardware solution provider at Seeed Studio, we offer an extensive array of networking products that support robust wireless connectivity options, including LoRaWAN, Amazon Sidewalk, Helium, and Cat-M. In the subsequent sections, we will delve into the specifics—definitions, advantages, limitations, and applications—of these four LPWAN technologies. Moreover, we will highlight Seeed Studio’s variety of networking products—from modules and development kits to fully assembled devices—within each connectivity type. Our goal is to empower developers with the tools and knowledge to select the most fitting LPWAN solutions, streamlining the creation of IoT applications with greater efficiency.

LoRaWAN: The Open Standard for Global IoT

LoRaWAN, short for Long Range Wide Area Network, is a protocol designed for the specific needs of low-power, long-range IoT applications and is governed by the LoRa Alliance. It utilizes LoRa modulation technology to enable communication across its network architecture, which is composed of four primary components. Operating on a star-of-stars topology, LoRaWAN allows end devices to connect with gateways, which then route information to a network server. This server acts as the control center, managing connections, authenticating devices, and orchestrating data transfer to the application servers. The distributed nature of LoRaWAN’s architecture supports a scalable network, capable of servicing countless devices across expansive regions with relatively few infrastructure demands.

LoRaWAN Network Architecture:
●End Nodes: These are the edge devices or sensors capturing data.
●Gateway: This component gathers data from multiple end nodes.
●Network Server: It aggregates data from the gateways to send to the application server.
●Application Server: This server processes and possibly visualizes the aggregated data.

Source: The Things Network

*For an in-depth exploration of LoRa and LoRaWAN, including differences and detailed network architecture, refer to our previous comprehensive post here.

LoRaWAN Pros & Cons

LoRaWAN, a key player in LPWAN technology, brings both benefits and limitations to the table. Its ability to communicate over multiple kilometers is invaluable in remote areas lacking conventional connectivity. The technology’s low power consumption allows for years of battery life, ideal for hard-to-reach deployment sites. LoRaWAN’s resilient and adaptable setup has led to its adoption in sectors such as agriculture, smart urban development, asset tracking, and environmental observation. Furthermore, the use of unlicensed frequencies helps to reduce operational expenses. However, the limited bandwidth narrows data transfer speeds, potentially making it unsuitable for high-throughput needs. Additionally, operating on an unlicensed spectrum raises the possibility of interference, which can affect network stability.

Applications of LoRaWAN

LoRaWAN’s typical applications span a multitude of scenarios, particularly those involving infrequent data transmission over wide areas. The technology’s cost-effective and expansive reach positions it as a prime solution for various IoT initiatives.

In smart agriculture, it enables remote soil moisture and climate condition monitoring.
For utility companies, smart meters track usage data with minimal human intervention.
Cities leverage LoRaWAN for managing street lights, waste collection, and parking.
In asset tracking, it facilitates the oversight of goods across vast distances, essential for supply chain management and wildlife conservation.

LoRaWAN Products Recommendation

To ensure the longevity and effectiveness of your LoRaWAN network, choosing high-quality hardware is crucial. Seeed Studio offers a comprehensive selection of production-ready modules, user-friendly development boards and kits, as well as robust industrial devices tailored for LoRaWAN ecosystems. Here are some top picks to help you build out your LoRaWAN End Nodes and Gateways:

LoRaWAN Gateways

SenseCAP M2 Multi-Platform LoRaWAN Indoor Gateway(EU868, US915, AS923, AU915, AS923-JP, EU868 4G, US915 4G)

SenseCAP LoRaWAN Outdoor Gateway (EU868, US915, AU915, AS923)

Wio-WM1302 Long Range Gateway Modules (EU868, US915 both available in format factors of SPI and USB)

WM1302 Raspberry Pi Hat to develop your LoRa gateway with Raspberry Pi

LoRaWAN Sensor Nodes

Wio-E5 LoRa Modules to Design Your LoRaWAN Sensor Nodes (it also comes with a low power consumption version Wio-E5-LE)

Grove-Wio-E5 Module to Extend the LoRaWAN connectivity to your Arduino or Rapsberry Pi

Wio-E5 LoRa Dev Kits (Mini +Dev Kit), open source dev platform coming with built-in AT command

Wio-WM1110 LoRa Tracker Module, a production-ready module powered by Semtech LR1110

Wio Tracker 1110 Dev Board, an Arduino compatible open source development board to build tracking PoCs

SenseCAP T1000 Tracker, a card-size LoRaWAN sensor node that collects data of location, temperature, light, motion

Wio-WM1110 Dev Kit, an advanced open-source dev platform with rich IOs

SenseCAP LoRaWAN Starter Kit, an all-in-one tool set of LoRaWAN gateway and Arduino-compatible sensor node kit

SenseCAP S210X LoRaWAN Series Sensor Devices, ready to deploy industrial sensors for collecting environmental and climate parameters.

Note: A full LoRaWAN Network system will require four key components: End nodes, gateway, network server and application server. To explore our full range of LoRaWAN products of end nodes and gateway, and find the best fit for your project, please visit their corresponding links!

●LoRa modules to build your own LoRaWAN end nodes (regular environmental sensors, trackers and more) and gateways.
●LoRa Dev boards and Dev Kits to build end nodes and gateway PoCs
●LoRa Sensor Nodes (Devices)
●LoRa Gateways
●LoRa Accessories of Antennas to enhance your gateway signal

Amazon Sidewalk: Bridging the Gaps in Urban Connectivity

Amazon Sidewalk represents a leap forward in low-power, wide-area network (LPWAN) technology, an initiative by Amazon to bolster wireless connectivity across urban areas. It enlists the participation of consumer devices like Amazon Echo and Ring as Sidewalk Bridges / Gateways. These bridges / gateways contribute a tiny slice of their internet bandwidth to form a mesh network using Bluetooth Low Energy (BLE), the 900 MHz band, and other frequencies. This network can carry encrypted data from Sidewalk-enabled devices such as smart locks and sensors to a Sidewalk Bridge, potentially up to half a mile away. Once the data reaches a bridge, it’s sent to the cloud through an internet connection, enhancing IoT device functionality across a more extensive range than conventional home Wi-Fi networks.

Amazon Sidewalk Architecture:
●IoT Endpoint Devices, Sidewalk-enabled devices that collect and send data.
●Sidewalk Gateways, Devices like Echo and Ring that serve as connection points.
●Cloud Services, Amazon’s cloud infrastructure that processes and manages the data flow.

Source: Amazon Sidewalk

Sidewalk Pros & Cons

Amazon Sidewalk’s innovative LPWAN connectivity offers several benefits but also poses potential drawbacks:

Pros:
●Extends connectivity beyond typical Wi-Fi ranges without extra infrastructure costs.
●Strong encryption protocols ensure secure data transmission.
●The shared network can offer more consistent coverage for smart devices.
●Sidewalk is designed to support a vast number of devices within its network.

Cons:
●Utilizes a portion of personal internet bandwidth, which might be a concern for some users.
●Dependent on community adoption for network efficacy.
●Data security and privacy concerns, despite Amazon’s encryption efforts.
●Currently limited to the US, with a focus on areas with high population density (accessible to over 90% of the US population, and you can check the Sidewalk Coverage map here).

Sidewalk Applications

Amazon Sidewalk’s applications are diverse, primarily enhancing connectivity for smart home and community safety devices:

●Home Security: Cameras and smart locks remain connected even at property boundaries.
●Tracking Devices: Helps locate items or pets that are outside the Wi-Fi range.
●Smart Home Devices: Outdoor lights, sensors, and other devices operate flawlessly, irrespective of their distance from the main router.
●Community Safety: Wildfire detectors and similar safety devices stay connected over large areas for prompt alerts.
●Communal IoT: Potential for community-wide applications like environmental monitoring and public infrastructure management.

Sidewalk Compatible Products Recommendation

We at Seeed Studio support the Amazon Sidewalk ecosystem with a specially curated selection of Sidewalk-compatible products. Our range includes MCUs, development boards, and complete devices designed to accelerate your project development on this innovative network.

LPWAN Asset Tracker Dev Kit for Amazon Sidewalk

XIAO nRF52840

SenseCAP T1000-S (to be released)

More details

Helium: Decentralized LPWAN Network

*Beginning in late 2023, the Helium Network incorporated both LoRaWAN and high-speed 5G connectivity. In the context of this post, ‘Helium Network’ refers specifically to the Helium LoRaWAN Network.

Helium, often referred to as The People’s Network, represents a paradigm shift in wireless networks. Fully compatible with LoRaWAN, Helium is a decentralized network that connects Internet of Things (IoT) devices to the Internet using the innovative LongFi technology. This technology merges the capabilities of LoRaWAN with the Helium blockchain, fostering a network that is not only extensive but also more accessible. With a strong foundation laid in 2013, Helium has been at the forefront of transforming the telecommunications landscape by relying on community-powered gateways. These gateways are critical in providing coverage and validating the network’s integrity through a unique proof-of-coverage model.

Source: helium

It differentiates from traditional LoRaWAN by incentivizing users to expand the network through mining HNT. This model has proven advantageous for creating extensive, user-operated networks. Helium’s applications are vast, including asset tracking and supply chain management, which Seeed Studio products are well-suited for.

Helium vs Traditional LoRaWAN

While Helium builds upon the LoRaWAN protocol, it introduces several distinctions compared to traditional LoRaWAN networks:

●Incentive Model: Helium provides a financial incentive for users to run hotspots / gateways to expand network coverage, which is not a feature of standard LoRaWAN networks.
●Decentralized Operation: Traditional LoRaWAN networks are typically operated by companies or organizations, whereas Helium’s infrastructure is created by individuals.
●Blockchain Integration: The use of blockchain for secure transactions and the distribution of rewards is unique to Helium.
●Scalability: Helium’s model allows for rapid growth and scalability since anyone can join the network by purchasing a Hotspot, whereas traditional LoRaWAN deployments often require significant planning and capital investment.
●Network Density: As more people participate by setting up Hotspots, Helium can potentially achieve a higher network density compared to standard LoRaWAN networks, which often have coverage gaps.

Helium Pros & Cons

The Helium Network presents an innovative model with several advantages and inherent challenges that influence its applications. On the upside, its decentralized structure democratizes network participation, allowing anyone to set up a Hotspot and expand the network, which incentivizes rapid network growth and potentially denser coverage. The use of blockchain ensures transparency and security, fostering trust in the network’s operations. Additionally, the low-power, long-range capabilities of the network make it ideal for a multitude of IoT applications, from tracking devices to environmental sensors, that require widespread and cost-effective connectivity. However, the reliance on individual participants for network infrastructure could lead to inconsistent coverage, and unstable network, depending on the distribution of Hotspots. The network’s novel approach also brings regulatory and technological uncertainties, as it must navigate evolving blockchain and telecommunications landscapes.

Typical Applications of Helium

The Helium Network’s unique properties facilitate a wide array of applications, primarily in the Internet of Things (IoT) sphere. Its low-power, long-range connectivity is ideal for smart devices that require intermittent data transmission over broad geographic areas.

In urban environments, it’s used for smart city projects, such as monitoring traffic flow, air quality, and public infrastructure.
In agriculture, farmers deploy sensors to track crop health and livestock, leveraging Helium’s extensive coverage even in rural areas.
Asset tracking is another significant application, with logistics companies utilizing the network to monitor goods in transit across large distances. The network also serves personal uses, such as pet tracking and home automation, connecting devices like smart locks and environmental sensors.
Moreover, in emergency response situations, the Helium Network can provide critical communication for devices when traditional networks fail.

The decentralized nature of the network ensures that these applications are backed by a robust, community-driven model, reducing reliance on single points of failure and offering a cost-effective solution for scalable IoT deployment.

Helium Compatible Products

To enable the community to embrace Helium’s unique ecosystem to build the decentralized network, we offer a full collection of compatible products of gateways, sensor nodes, and accessories.

SenseCAP M1 LoRaWAN Gateway (EU868, US915, AS923, AS923-JP)

SenseCAP M2 Light Hotspot for Helium, which transmits the data to LNS via Helium network

SenseCAP M4 Square for Helium, Flux, and MysteNodes

SenseCAP T1000 LoRaWAN GPS Tracker,

SenseCAP S210X Series LoRaWAN Sensor Nodes

Cat-M: Low-Power Cellular Connectivity for IoT

Category M1 (Cat-M) is a low-power wide-area (LPWA) technology developed under the LTE standard for Internet of Things (IoT) and machine-to-machine (M2M) communications. It represents a middle ground by offering better data rates than traditional LPWAN technologies while ensuring greater efficiency than standard LTE.

Source: f5.com

Operating within the existing LTE infrastructure, Cat-M utilizes a reduced bandwidth of 1.4 MHz, in contrast to the 20 MHz typical of higher-speed LTE connections. This narrower bandwidth reduces module complexity which, in turn, cuts power consumption and costs. Cat-M’s key features include Voice over LTE (VoLTE), full-duplex communication, and handover for mobile applications, which is not universally supported across LPWA technologies. Additionally, it boasts enhanced coverage up to 15 dB better than standard LTE, enabling connectivity in difficult environments. Its suitability for IoT applications is evident in scenarios where small amounts of data need to be reliably transmitted over extended periods on a single battery, such as wearable medical devices, smart utility meters, and industrial sensors.

Cat-M Pros & Cons

Cat-M technology presents a balance of benefits and limitations suitable for specific IoT applications. Here are its pros and cons:
Pros:
●Extended coverage enabling connectivity in remote and indoor environments
●Lower power requirements for longer battery life, extending operation time to several years
●Support for VoLTE and mobility with handover, offering versatility for a range of IoT devices

Cons:
●Lower data transmission rates compared to traditional LTE
●Dependence on the availability and coverage of LTE networks, potentially limiting use in some remote areas

Cat-M Applications

Cat-M is well-suited for a variety of applications where devices transmit occasional updates or small data packets over long periods without human intervention. They include:
●Smart Meters: Periodic transmission of utility usage data
●Agricultural Sensors: Monitoring of soil moisture and environmental conditions in remote fields
●Wearable Health Devices: Tracking patient vitals and providing alerts to healthcare providers
●Smart City Infrastructure: Controlling street lighting, monitoring parking spaces, and collecting environmental data
●Asset Tracking: Monitoring the location and status of goods in transit, benefiting from mobility support

Head-to-Head Comparison

When selecting the right IoT network solution, we always think about the network range, data rates, battery life, costs, scalability, and security. To help you get a clearer comparison, I’ve created a comparison table of the LPWAN networks of LoRaWAN, Amazon Sidewalk, Helium, and Cat-M in terms of range, data rates, battery life, costs, scalability, and security. I hope this comparison table will be the guide that you turn to to decide the connectivity for your future LPWAN projects.

	LoRaWAN	Amazon Sidewalk	Helium	Cat-M
Range	Up to 15 km in rural areas, 2-5 km in urban settings	Up to 800 meters with the ability to extend through a mesh network	Similar to LoRaWAN, potentially greater with dense network deployment	Typically less than LoRaWAN, around 1-10 km
Data Rates	Between 0.3 kbps to 50 kbps	Designed for small packets; exact data rates not publicly detailed	Similar to LoRaWAN, approximately 0.3 kbps to 50 kbps	Higher than the other LPWANs; 300 kbps to 1 Mbps
Battery Life	Optimized for long battery life, typically over 10 years	Designed for years of battery life but dependent on device usage	Comparable to LoRaWAN; designed for long battery life	Less than LoRaWAN/Helium, but better than traditional cellular (LTE)
Costs	Low infrastructure cost due to open standard; device costs vary	Low-cost due to shared community bandwidth; no direct fee for users	Low entry cost; incentivized expansion through cryptocurrency rewards	Moderate; requires cellular infrastructure, subscription fees may apply
Scalability	High; can support millions of nodes	Low; depends on user adoption and density of Sidewalk Bridges, and it’s only available in the US Urban area	High; user-operated nodes with decentralized growth	Medium; depends on existing cellular infrastructure, which doesn’t support expansion by individual or organization.
Security	Strong with built-in end-to-end AES-128 encryption	Three layers of encryption, and not reliant on device manufacturers for security updates	Uses blockchain for secure transactions, but specific IoT security measures depend on application	High-grade security due to cellular network standards (SIM-based authentication and encryption)

The Future of LPWAN Technologies

As the Internet of Things (IoT) continues to expand, Low Power Wide Area Network (LPWAN) technologies are set to play a pivotal role in its evolution. Here are some trends that I believe will likely shape the future of LPWAN:
●Greater Interoperability: Standardization efforts will likely lead to improved interoperability between different LPWAN technologies, making it easier for devices to communicate across various networks and platforms.
●Growth in LPWAN-as-a-Service: The emergence of LPWAN-as-a-Service models will allow businesses to deploy IoT solutions without investing in the underlying network infrastructure, lowering the barrier to entry.
●Improved Security & Privacy: As LPWAN technologies become more widespread, there will be an escalated focus on enhancing security measures to protect sensitive data transmitted across these networks.
●Killer Application Smart City: LPWAN will continue to be a driving force behind smart city initiatives, powering everything from street lighting and traffic management to waste management and environmental monitoring.
●Enhanced Battery Life: With the development of more energy-efficient chipsets and protocols, the battery life of LPWAN-connected devices will extend significantly, reducing maintenance costs and enabling more sustainable IoT solutions.
●Integration with Machine Learning and Edge Computing: The convergence of edge computing with LPWAN technologies will increasingly enable local data processing at the network’s edge, which conserves bandwidth and minimizes latency by reducing the need for long-distance data transmission. Simultaneously, the integration of AI and machine learning will significantly enhance LPWAN’s capabilities, allowing for predictive analytics and smarter, real-time decision-making processes. These advancements will jointly elevate the efficiency and effectiveness of IoT applications, leading to more autonomous and responsive systems within the LPWAN infrastructure.

Conclusion

The emerging LPWAN technologies—LoRaWAN, Amazon Sidewalk, Helium, and Cat-M—are key enablers of the IoT landscape, each with distinctive features. In comparing these technologies, we’ve seen that trade-offs exist between range, data rates, battery life, and costs. More importantly, these technologies will respectively find their niches, with improvements in technology driving forward the potential for innovative IoT applications that are more efficient, intelligent, and integrated.

LPWAN Frequently Asked Questions

What is the main advantage of LPWAN?
LPWAN technologies are designed for long-range communication with minimal power consumption, making them ideal for IoT applications where devices need to operate on battery power for extended periods.

How does LoRaWAN® differ from traditional Wi-Fi or cellular networks?
LoRaWAN is optimized for lower power consumption and longer range at the expense of data rate, whereas Wi-Fi and cellular networks offer higher data rates but consume more power and typically cover shorter distances.

Can Amazon Sidewalk be used for industrial IoT applications?
Amazon Sidewalk is primarily designed for consumer and smart home devices. Its use in industrial IoT is limited due to its lower bandwidth and reliance on residential infrastructure.

What makes Helium unique in the LPWAN market?
Helium’s unique selling point is its decentralized network model, which uses blockchain technology to incentivize network growth and security.

Is Cat-M suitable for mobile IoT devices?
Yes, Cat-M supports mobility and is suitable for applications like vehicle tracking and wearables, offering a balance between power efficiency and data rate with added voice support.

How do I choose the right LPWAN technology for my project?
Consider the range, data rate, power consumption, and specific application requirements of your project. Also, factor in the existing infrastructure and the total cost of ownership. Consulting with industry experts like Seeed Studio can provide tailored advice for your IoT solutions.

If you have further questions or want to dive deeper into the world of LPWAN technologies, feel free to reach out to us at iot(at)seeed.cc or share your thoughts in the comments below.

Resources:

Attributions:

The LoRa® Mark is a trademark of Semtech Corporation or its subsidiaries.
LoRaWAN® is a mark used under license from the LoRa Alliance®.

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Chaihuo Makerspace Joins Fab Academy as a 2024 Node!

Alison Yang — Wed, 17 Jan 2024 10:03:37 +0000

Exciting news! Chaihuo Makerspace has taken an exciting step forward by applying to become a node of the Fab Academy course for 2024, empowering students to “how to make almost anything!”. As the pioneering maker space in Shenzhen, Chaihuo, a subsidiary of Seeed Studio, opens its doors to community makers providing a range of tools, materials, and cutting-edge technologies help them to accomplish their projects.

What is the Fab Academy? It’s a rigorous five-month-long program, where creativity meets digital prowess. Here, students are immersed in a process of learning to visualize, design, and create prototypes using an assortment of digital fabrication tools. More than just an educational course, the Fab Academy is a multi-disciplinary boot camp that instills a ‘learn-by-doing’ ethos, encouraging the creation of tangible items that can contribute to sustainable communities and cities.

Participants are taken on a transformational journey, converting codes into physical masterpieces. Upon completion, students don’t just walk away with knowledge; they earn a Fab Diploma—a culmination of various Fab Academy Certificates, where the emphasis is on skill acquisition, not just the time spent or the credits earned.

Worth mentioning that we are profoundly honored to have Salman Faris as our instructor this year. He is a co-founder of MakerGram as well as the honorable Seeed Studio Ranger, not only passionate for electronics and hardware product development, but also got diploma in digital fabrication from the prestigious Fab Academy.

Looking ahead, we’re gearing up for this year’s Fab24 event in Mexico, where we extend our best wishes to all our students, confident that they will achieve excellent results!

The post Chaihuo Makerspace Joins Fab Academy as a 2024 Node! appeared first on Latest Open Tech From Seeed.

Announcing the Champions of the OpenCV AI Competition 2023

Alison Yang — Tue, 16 Jan 2024 07:29:36 +0000

We’ve been following the amazing journey of the “OpenCV AI Competition 2023” on Hackster. The competition was a resounding success, pulling 177 project submissions and welcoming over 1500 developers. As a sponsor for the competition, we are glad to provide valuable coupons for the 23 winners. The anticipation culminated on December 28th when the winners were unveiled during a much-anticipated live reveal on the OpenCV livestream (watch the announcement at OpenCV Live). After much deliberation, exceptional winners emerged in two distinct award categories.

With no further ado, let’s dive into the highlight reel and spotlight six spectacular projects that not only wowed the judges but also won the hearts of the community.

FREISA – Four-legged Robot Ensuring Intelligent Sprinkler Automation by
Team B-AROL-O: Gianpaolo Macario, Gianluca Teti, Pietro d’Agostino, Davide Macario, Andrea Podo, Orso Eric: The B-AROL-O Team’s epic saga continues with FREISA. It’s a four-legged robotic marvel that’s transforming the agriculture industry with its intelligent sprinkler automation.
OpenCV for Exoplanet Detection by Katelyn Gan: This groundbreaking project took a giant leap into the cosmos. By harnessing OpenCV, this proof-of-concept demonstrates how we can detect the subtle radial velocities of stars, bringing us one step closer to finding our Earth 2.0.
IC4U – Robot Guide Dog for the Visually Impaired by selinoid: IC4U is reimagining mobility aids for the visually impaired. This robotic guide dog harnesses the power of AI and machine learning to offer the same assistance and companionship of a real guide dog.

Popular Vote Prizes

Opti Sentinel by Team Robixlo: Muhammad Awab, Maryam Riaz, Ali Raza, Kinza Noreen: Meet your new robotic companion in the field, designed to be a diligent sentinel watching over vast landscapes.

Guiding Gaze by Team Optical Oddballs: Tejeswar Pokuri, Aryaman Sharma, HARSHITA, manan gaur: This smart solution offers a new outlook for the blind, solving an age-old problem with the latest technology.

In particular, we’d like to shine a spotlight on “Rescue Bot,” a groundbreaking innovation by Muhammed Zain, Vishnuraj A, which truly encapsulates the spirit of resilience. This autonomous rover has been meticulously engineered to navigate through the challenging terrains of disaster-stricken areas, with the noble mission of locating survivors and enhancing disaster relief efforts. What’s especially gratifying for us at Seeed is seeing our hardware in action within this project. The creators integrated the Grove series sensors and the Wio Terminal into their design, showcasing the real-world impact our products can have in critical situations. It is incredibly rewarding to witness community members utilize our sensors and technology, contributing their ingenuity to the community and completing a full circle of innovation and practical application.

In closing, our hats off to all the winners of the OpenCV AI competition! Your innovative contributions not only showcase extreme talent but also fuel the vibrant and ever-growing spirit of creativity in our community. Your efforts have solidified that our investment in innovation is indeed making waves!

More Read

Unleash the potential for Raspberry Pi Edge Devices with OpenCV

Since 2018, Seeed has become an officially approved design partner and reseller for Raspberry Pi. In the field of OpenCV, Seeed has developed 5 comprehensive wikis to take a step with reTerminal (Seeed’s Raspberry Pi-powered HMI) and Pi Camera with OpenCV:

Dive Deep into Vision AI and Kickstart Your Next AI Application

Check out our vision AI resource hub powered by the NVIDIA Jetson platform to unlock vision AI insights, including a rich set of crucial AI development tools, practical computer vision demos and community projects, powerful industrial case stories, and the latest AI news. Check out Jetson Platform 2023 Roundup to win a reComputer J4012 now!

Until next time!

The post Announcing the Champions of the OpenCV AI Competition 2023 appeared first on Latest Open Tech From Seeed.

Introducing Maker Camp in Shenzhen

Ellie Cai — Mon, 15 Jan 2024 11:30:17 +0000

Maker culture has been on the rise in recent years, and Shenzhen has been leading the way in innovation. Each year, Seeed Studio and Chaihuo Makerspace welcome global makers to explore Shenzhen’s tech ecosystem and abundant community resources. At the beginning of 2024, Seeed Studio officially launches the “Maker Camp in Shenzhen” program, an international innovation initiative aiming to integrate Shenzhen’s abundant supply chain resources, electronic technology facilities, rapid prototyping capabilities, and extensive open-source community network, providing an unparalleled platform for in-depth collaboration and project implementation for university teams and innovation practitioners worldwide.

Maker Camp in Shenzhen is a unique opportunity for makers to explore the tech ecosystem in Shenzhen and engage in hands-on learning experiences while creating open-source, hardware-based projects that can positively impact society.

What's in the Mix?

Dreaming of leveraging world-class supply chains, electronic technologies, rapid prototyping services, and a rich open-source community for your project or research? “Maker Camp in Shenzhen” connects your dreams with the limitless possibilities of Shenzhen. Participants in the project will have the opportunity to understand the intricacies of manufacturing processes and supply chain management, learning how to harness these resources to create innovative projects. By sharing their knowledge and developments, they can empower the maker community to learn from their experiences.

Maker Camp in Shenzhen is not just about creating innovative projects – it also offers workshops, hackathons, and other sessions to help participants experience the latest in technical solutions and hone their skills. Additionally, participants will collaborate with talented makers from around the world, sharing knowledge, skills, and building a global network of support.

We cherish the sharing and inheritance of each innovative story. Each team participating in “Maker Camp” will document their experiences on GitHub with a unique number (e.g., “2401”, “2402”, “2501”), creating valuable digital footprints and providing a treasure trove of practical experience and learning for the global maker community.

What Seeed Offers

Our Offerings Include, but Are Not Limited To:

Factory Visits: In-depth understanding of the processes and logic behind manufacturing.
Technical Training: Providing participants with hands-on experience of the latest technological solutions through workshops and Hackathons.
Co-Create: Potential opportunity to transform your creative ideas into profitable products.
Sharing and Summary: Acting as a bridge for project sharing and connecting with potential collaborators.

Excited? Join us now and unlock a world of possibilities!

Sharing is Caring!

The program aims to unite makers in exploring Shenzhen’s tech ecosystem, participating in hands-on learning experiences, and collaboratively crafting open-source hardware projects with a positive societal impact. Crucially, we encourage everyone to actively participate by documenting and sharing their Shenzhen experiences, whether related to manufacturing, supply chain, academic knowledge, new materials, or developments (words, photos, videos—all forms of expression are welcomed). This collective effort empowers the community to glean insights and knowledge from diverse experiences.

All contributions will be showcased on Seeed Studio’s GitHub Channel.

How to Participate?

Prepare your ideas, form your team, and head to our official site to register. We can’t wait to see your creative sparks shining in Shenzhen!

Guidelines for Content Organization and Contribution

We encourage participants to adhere to a standardized naming convention and categorization when uploading their content to GitHub. The suggested naming format is “Participation Term – Organization-Name,” for example, “2401-MIT-Ellie.” In terms of categorization, we recommend organizing content under specific themes like factory production, electronic resources, community resources, or other observations. This practice ensures clarity, consistency, and efficient organization of shared information.

Additionally, if you come across any original documents with missing sections and wish to enhance them, please don’t hesitate to reference that document in your uploaded content. Your contributions to improving and completing the existing documentation are highly valued.

That concludes today’s update! Get ready for an exciting announcement – the first episode of Maker Camp in Shenzhen, labeled as “2401,” is on its way to you very soon. Stay connected and keep an eye out for more updates!

The post Introducing Maker Camp in Shenzhen appeared first on Latest Open Tech From Seeed.

Webinar: Leveraging LoRaWAN in Tracking Solutions for Healthcare

Kezang Loday — Mon, 15 Jan 2024 04:53:48 +0000

In today’s rapidly evolving healthcare landscape, GPS tracking technology has emerged as a powerful tool with numerous applications, tracking medicine shipments, enhancing asset management and patient care.

To get a deep dive into the tracking solutions in healthcare, we’re partnering with 2 of our long-term partners LORIOT, Traxmate to have a webinar centering around “Leveraging LoRaWAN in Tracking Solutions for Healthcare”. On February 2nd, join 3 of our professional speakers to get valuable insights into the game-changing benefits and applications of LoRaWAN technology in the healthcare industry. Discover the critical role that smart tracking solutions play in advancing asset management and ensuring personnel safety.

Industry leaders Ingi Diego, Kevin Yang, and Andreas Ekengren, will share their expertise industry insights, knowledge know-how, and technical breakdowns of LoRaWAN tracking solutions.

Speakers:

Ingi Diego

Business Development Manager

LORIOT

Kevin Yang

Product Director

Seeed Studio

Andreas Ekengren

VP Business Development

Traxmate / Combain Mobile AB

In the webinar you will also witness a live demonstration showcasing the practical application of LoRaWAN tracking solutions at Lunds University Hospital in Sweden. The demo, featuring SenseCAP T1000 LoRaWAN Trackers, integrated with Traxmate’s tracking platform and LORIOT LoRaWAN Network, showcases improved visibility of high-value medical equipment and enhanced emergency response services. You will see how it enables location tracking of patients and medical equipment, both indoors and outdoors.

Finally, attendees will have the opportunity to engage in a live Q&A session with the experts. Register now to reserve your spot and dive into the power of LoRaWAN smart tracking solutions in the healthcare industry!

Webinar Details:

Location: Online

Date: 2nd February, 2024 Friday

Time: 05:00 – 06:00 PM GMT+8

The post Webinar: Leveraging LoRaWAN in Tracking Solutions for Healthcare appeared first on Latest Open Tech From Seeed.

Generative AI at the Edge Fundamentals: What is it and how it works?

Jennie Wang — Fri, 12 Jan 2024 12:13:13 +0000

The next significant breakthrough in modern AI came with the advent of GPT(Generative Pre-trained Transformer). Leveraging vast amounts of data from the internet, the core technology of GPTs has enabled AI models to be more generalized. Without the limitation of conventional AI approaches like heavily relying on predefined rules and patterns, or even letting machines make predictions based on the relationship between data and label it learned. In the Generative wave, we can make the results flexible and infinite by only tapping or verbally providing a prompt to the machine, making life more convenient and smarter. Now, let’s dive deep to figure out how to understand generative AI at the edge, and what we can do with generative AI!

What is Generative AI？

Generative AI is designed to learn from patterns in unstructured data based on deep-learning neural networks. Employing a blend of unsupervised and semi-supervised methods in its initial training, it also seamlessly integrates supervised techniques during fine-tuning. It enables the model to autonomously craft new, original content with enhanced efficiency and precision across various domains—be it text, images, audio, or synthetic data. Discover our Generative AI website for more insights.

Generative AI Architecture Underneath

The concept of Generative AI, which refers to a pre-trained model that serves as the starting point for various downstream tasks, utilizes the Transformer as the underlying architecture, where the foundation model is built and pre-trained with a huge amount of data. Once pre-trained, the model can be fine-tuned for specific tasks or used as is for various creative applications, such as language generation, text completion, or even image synthesis.

Transformer

The Transformer framework is a groundbreaking architecture in natural language processing, characterized by its encoder-decoder structure and self-attention mechanism with the whole input rather than processing vectors one by one in order.

The transformer model architecture. Image from paper “Attention Is All You Need”

In the encoder, the input sequence undergoes multi-head self-attention, allowing the model to focus on different parts of the sequence simultaneously. The decoder, responsible for generating the output sequence, utilizes a similar mechanism while incorporating additional components like positional encoding to maintain the order of words. Feedforward neural networks within each layer process the information derived from attention mechanisms, enabling the model to capture complex relationships in the data. Additionally, layer normalization and residual connections contribute to stable and efficient training, allowing the model to effectively learn intricate patterns in sequential data.

Foundation Model

Understanding the framework of a foundation model involves recognizing its role as a pre-trained model that serves as a starting point for various downstream tasks.

Take an example of language models like GPT, the foundation model is trained on an extensive and diverse dataset using unsupervised learning. During this pre-training phase, the model learns the nuances of language, capturing contextual relationships and patterns. The resulting foundation model is then fine-tuned for specific tasks or applications, adapting its pre-learned knowledge to address more specialized challenges.

This pre-training followed by fine-tuning approach empowers the foundation model to excel in a wide range of language-related tasks, from text completion to sentiment analysis. Let’s take a look at some classic foundation models that can be deployed at the Edge:

LLM: or “Large Language Model,” is a powerful artificial intelligence model in the context of natural language processing and machine learning. Trained extensively on diverse textual data, it excels in comprehending and generating human-like language. This versatile model can be finely tuned to cater to specific language tasks or domains. One significant application of LLM should be Llamaspeak, an innovative interactive chat application that utilizes live NVIDIA Riva ASR/TTS technology, allowing users to engage in vocal conversations with a locally running LLM, enhancing the interactive and dynamic nature of communication. Check out our wiki about how to build a local chatbot by deploying Riva and Llama2 on reComputer.

CLIP: stands for Contrastive Language-Image Pretraining, is a computer vision model developed by OpenAI. It excels in understanding the relationship between images and their corresponding textual descriptions, built on a large body of work on zero-shot transfer, natural language supervision, and multimodal learning. With CLIP, You only need to define the possible prompts or descriptions the objects of the scene belong to, then CLIP will help you predict the most probable class for the given image or video based on its extensive pertaining. One illustrative application of CLIP could be automating labeling processes using Vision Transformers (OWL-ViT) in conjunction with CLIP. It enables zero-shot object detection and classification, not only just streamlining the labeling workflow, but also extending the model’s capabilities to classify objects it has never encountered before.

Generative AI Model Types

Text-to-Text

Text-to-text models seamlessly transform natural language inputs into corresponding text outputs. Specifically trained to understand and generate mappings between text pairs, these models offer a versatile toolkit applicable across a spectrum of tasks, such as multilingual translation, concise document summarization, efficient information extraction, precise search operations, dynamic content clustering, and even nuanced content editing and rewriting

Text-to-Image

Text-to-image models represent a novel frontier in AI, training on extensive datasets comprising images paired with concise text descriptions. Leveraging methodologies like diffusion, by progressively refining the model’s understanding of the intricate relationship between textual prompts and corresponding visual features, these models excel in translating textual prompts into vibrant visual outputs. A prime application lies in the area of image generation and editing, where the model’s capacity to comprehend and manifest visual concepts from textual cues enhances creativity and efficiency.

Text-to-Task

Text-to-task models are meticulously trained to execute precise actions or tasks in response to textual input. These tasks encompass a broad spectrum, including answering queries, conducting searches, making predictions, and undertaking various other actions. These models find versatile applications in virtual assistants, where their capabilities streamline interactions, and in automation, where their proficiency in understanding and responding to text prompts enhances operational efficiency.

What’s Next? Ready for Practical Applications?

To perform these GenAI tasks smoothly at the edge, NVIDIA Jetson is capable of locally running large language models (LLMs), vision transformers, and stable diffusion efficiently and stably. That includes the largest Llama-2-70B model on Jetson AGX Orin, and Llama-2-13B at interactive rates. Powered by the great Jetson Orin NX with up to 100 TOPS AI performance, our reServer Industrial J4012 edge device hands over the capability to perform on-site video analytics tasks seamlessly. As an expendable local storage with 2 drive bays for 2.5″ SATA HDD/SSD, it combines with 5 GbE RJ45 ports where 4 of which are for 802.3af PSE, making it an ideal choice to deploy local large language models with real-time processing through multiple streams.

You can simply use miniGPT-4 to create writing content, generate image descriptions, deploy virtual conversational agents, and even get websites from handwritten drafts.

While dealing with environmental perception, Vision2Audio based on the LLaVA model, brings the gap between vision and sound together, allowing visually impaired individuals to perceive the surrounding environments by verbal instructions.

To comprehend multimodal input, you can use CLIP to generalize across diverse classes through zero-shot learning. It performs great in a spectrum of tasks, from classifying images based on textual descriptions to retrieving images with specific textual queries. Its capabilities extend to object detection, text-based image generation, and various natural language processing endeavors such as sentiment analysis and visual question answering, growing as a powerful tool for AI applications requiring a nuanced comprehension of both image and text data. Check out the demos of how to deploy CLIP on reComputer Jetson Orin NX.

Free Trail Virtually for NVIDIA Jetson AGX Orin Developer Kit!

Ready to dive into your first generative AI application? Schedule a complimentary virtual trial with our NVIDIA Jetson AGX Orin Developer Kit. Unleash your creative ideas into the physical world with cutting-edge GenAI technology!

Seeed: NVIDIA Jetson Ecosystem Partner

Join the forefront of AI innovation with us! Harness the power of cutting-edge hardware and technology to revolutionize the deployment of machine learning in the real world across industries. Be a part of our mission to provide developers and enterprises with the best ML solutions available. Check out our successful case study catalog to discover more edge AI possibilities!

Take the first step and send us an email at edgeai@seeed.cc to become a part of this exciting journey!

Download our latest Jetson Catalog to find one option that suits you well. If you can’t find the off-the-shelf Jetson hardware solution for your needs, please check out our customization services, and submit a new product inquiry to us at odm@seeed.cc for evaluation.

The post Generative AI at the Edge Fundamentals: What is it and how it works? appeared first on Latest Open Tech From Seeed.

Pose Landmark Detection on Raspberry Pi-powered HMIs at the Edge

Kasun Thushara — Fri, 12 Jan 2024 10:11:51 +0000

Introduction

In the realm of edge computing, integrating pose landmarks detection on Raspberry Pi devices is a game-changer. This computer vision technique, identifying key body points for posture analysis, enhances real-time processing on compact systems. Beyond showcasing the computational capabilities of Raspberry Pi, this integration enables responsive human-computer interaction, health monitoring, and efficient surveillance in constrained spaces. The shift towards edge-based pose detection marks a transformative leap, making these devices essential in decentralized, responsive computing applications.

Why perform pose landmarks detection at the Edge?

Real-time Processing:
- Edge devices enable real-time processing, crucial for applications like gesture-based interaction, fitness tracking, and surveillance, where immediate response is essential. Cloud-based solutions may introduce latency due to data transfer and processing delays.
Reduced Latency:
- Processing data locally at the edge minimizes latency, ensuring quicker and more responsive applications. This is particularly critical for applications requiring instantaneous feedback, such as virtual reality or robotics.
Bandwidth Efficiency:
- Edge computing reduces the need for constant data transfer to the cloud, optimizing bandwidth usage. This is beneficial for applications with limited bandwidth availability or in scenarios where constant cloud connectivity is impractical.
Privacy and Security:
- Processing sensitive data locally enhances privacy by minimizing the need to transmit personal information to the cloud. This is crucial for applications like healthcare or surveillance, where data security and privacy are paramount.
Offline Functionality:
- Edge devices can operate independently of a continuous internet connection, ensuring functionality in environments with intermittent or no connectivity. This is especially valuable in remote or mobile settings.

Deploy in Raspberry Pi-powered Seeed Studio’s Solutions

Seeed Studio has introduced diverse variations of Edge Human Machine Interface (HMI) devices with built-in cameras, showcasing the feasibility of integrating pose landmarks detection. Our Application Engineers routinely update our knowledge base, and in our latest wiki update, we delve into the integration of MediaPipe for pose landmarks detection. This task proves invaluable in identifying key body locations, conducting posture analysis, and categorizing movements. The output provides body pose landmarks in both image coordinates and 3-dimensional world coordinates. Utilizing the lite model, we achieve a commendable 5-6 frames per second, balancing efficiency and accuracy. This enhancement in our technology portfolio reinforces our commitment to delivering cutting-edge solutions for real-time applications, particularly those requiring swift and precise analysis of body movements and postures.

Learn More

Applications of Pose Landmarks detections

Human-Computer Interaction (HCI):
- Pose landmarks detection is crucial for enhancing HCI in applications such as gesture-based control systems, allowing users to interact with devices through intuitive body movements.
Fitness and Health Monitoring:
- Pose landmarks detection is employed in fitness and health applications to analyze body postures during exercises, yoga, or physical therapy. It helps users maintain proper form and track progress.
Occupational Health and Safety:
- Pose landmarks detection can be applied in industrial settings to monitor workers’ postures and movements, helping prevent musculoskeletal disorders and enhancing workplace safety.
Education and Training:
- Pose detection is used in educational applications for virtual classrooms and training simulations, enabling interactive and immersive learning experiences.
Assistive Technologies:
- Pose detection is applied in assistive technologies to aid individuals with disabilities by translating their body movements into control commands for computers or other devices.

Seeed Studio’s Raspberry Pi Ecosystem

Seeed Studio has been serving the Raspberry Pi user community since 2013 and took the lead to join the approved reseller and design partner. Since the first version of reTerminal in 2021, we have a series of products including reRouter, edge controller series, and this year reTerminal DM, serving creators, makers, enthusiasts, students, engineers, enterprises as well as industries, and every scenario needing Raspberry Pi.

More Resources

Explore more products, full system devices, customization services, and use cases on the Seeed Raspberry Pi page.
Download our latest Raspberry Pi success case booklet to know how Seeed and Seeed’s Raspberry Pi-powered products and solutions assist in tackling real-world challenges. Share your idea and story with our team at edge@seeed.cc.
Dive deep into our Raspberry Pi wiki page to get yours started.
Download our latest product catalog to find the ones that suit your needs.
Wants to discuss more customization possibilities, please check out our customization services, and submit your inquiry to edge@seeed.cc to have a deeper discussion and evaluation for you.

The post Pose Landmark Detection on Raspberry Pi-powered HMIs at the Edge appeared first on Latest Open Tech From Seeed.

Edge-Enhanced Face Detection: A Deep Dive with Raspberry Pi-Powered Devices

Kasun Thushara — Thu, 11 Jan 2024 10:36:32 +0000

Introduction

In the dynamic realm of technology, edge computing has emerged as a game-changer, revolutionizing the way applications operate. Within this technological shift, face detection at the edge takes center stage, offering unparalleled efficiency and immediacy. This guide explores the crucial role of face detection in an edge computing environment, addressing the demand for real-time processing and heightened privacy. We’ll delve into methodologies, such as the Haar cascade method, and cutting-edge machine learning libraries like Google Media Pipe, shedding light on how this fusion is transforming industries.

Why Face detection at Edge is important?

Low Latency:
- Reduces processing delays by executing face detection closer to the data source.
- Enables real-time applications, such as security surveillance and responsive user interfaces.
Privacy Enhancement:
- Minimizes the need for transmitting sensitive facial data to external servers or the cloud.
- Addresses growing privacy concerns by keeping data processing localized.
Real-time Processing:
- Facilitates immediate decision-making in applications like security, retail analytics, and healthcare.
- Enhances the overall responsiveness and effectiveness of face detection systems.
Edge Computing Efficiency:
- Utilizes edge computing resources efficiently, optimizing the allocation of processing power.
- Reduces the burden on central servers, leading to more scalable and cost-effective solutions.
Security and Surveillance Improvements:
- Strengthens security systems by enabling quick and accurate identification of individuals.
- Enhances surveillance capabilities in monitoring crowded spaces and public areas.

When it comes to face detection, choosing between the Haar cascade method and machine learning libraries like Google MediaPipe involves considering various factors.

Haarcascade Method:
- Efficiency:
  - Utilizes predefined features for efficient face detection.
  - Computationally less intensive, suitable for real-time applications with limited resources.
- Robustness:
  - Reliable in straightforward scenarios with clear facial features.
  - Well-suited for applications where adaptability is not a primary concern.
- Resource-Friendly:
  - Requires less computational power, making it suitable for resource-constrained environments.
  - Ideal for applications with simpler face detection requirements.
Google Media Pipe:
- Machine Learning Precision:
  - Leverages machine learning for more accurate and sophisticated face detection.
  - Adapts to diverse facial features, enhancing precision in complex scenarios.
- Adaptability:
  - Learns and evolves, making it suitable for applications with varying facial characteristics.
  - Excels in scenarios demanding advanced and adaptable face detection capabilities.
- Complex Scenarios:
  - Particularly effective in scenarios with challenging lighting conditions, angles, or occlusions.
  - Provides superior performance in applications requiring nuanced facial feature recognition.

Figure: Face Detection with Media-Pipe

Learn More

Figure: Face Detection with Haar Cascade Method

Learn More

What are the applications of Face Detection?

Security and Surveillance

Face detection at the edge is crucial for security and surveillance due to its real-time threat detection capabilities, ensuring immediate identification of individuals for quick response to potential threats. Privacy protection is enhanced as facial data is processed locally, complying with regulations and reducing privacy concerns. The approach allows for scalable and efficient resource allocation, distributing processing tasks and optimizing system scalability. Face detection at the edge is adaptable to various environments, offering flexible deployment options, weather resistance, and operational continuity in the face of network failures. Reduced network dependency minimizes bandwidth usage and ensures uninterrupted surveillance operations.

Retail Analytics

In retail, face detection at the edge contributes to personalized customer experiences through real-time analytics and targeted marketing strategies. The technology improves security and loss prevention by integrating facial recognition to identify shoplifters and prevent fraudulent activities. Efficient queue management is achieved through real-time footfall analysis, enabling optimized staff deployment and better customer service. The technology also optimizes inventory management by tracking customer movements for dynamic inventory control and placement. In terms of data privacy compliance, local data processing ensures adherence to regulations, and transparent consent mechanisms address privacy concerns, fostering customer trust.

Seeed Studio’s Raspberry Pi Ecosystem

More Resources

Explore more products, full system devices, customization services, and use cases on the Seeed Raspberry Pi page.
Download our latest Raspberry Pi success case booklet to know how Seeed and Seeed’s Raspberry Pi-powered products and solutions assist in tackling real-world challenges. Share your idea and story with our team at edge@seeed.cc.
Dive deep into our Raspberry Pi wiki page to get yours started.
Download our latest product catalog to find the ones that suit your needs.
Wants to discuss more customization possibilities, please check out our customization services, and submit your inquiry to edge@seeed.cc to have a deeper discussion and evaluation for you.

The post Edge-Enhanced Face Detection: A Deep Dive with Raspberry Pi-Powered Devices appeared first on Latest Open Tech From Seeed.

Year in Review: Seeed Studio in 2023 — A Symphony of Innovation, Growth and Unforgettable Moments!

Ellie Cai — Fri, 05 Jan 2024 09:28:41 +0000

It’s that time again – the close of yet another eventful chapter, and what a ride it has been! As we bid farewell to 2023, we find ourselves reflecting on the experiences and achievements that have defined this remarkable year.
In 2023, Seeed Studio remains committed to our mission of being the most integrated platform for creating hardware solutions for IoT, AI, and Edge Computing application scenarios. Our vision is to become the most reliable hardware platform and empower everyone to achieve their digital transformation goals. Behind the scenes, Seeed Studio has undergone significant updates at every level. From dedicated investments in product innovation, expanding partnership to broaden our horizons, venturing into new territories, and embracing the excitement of learning something new each day… we’ve laid a solid foundation for the exciting developments to follow.

Buckle up, because we’re about to take you on a journey through the highlights that made 2023 truly unforgettable.

Long Blog Alert: A Patient Read Ahead

I. Infinite Innovation: New Products and Technologies

In the past year, Seeed Studio continued our unwavering commitment to innovation. We proudly introduced a multitude of exciting new devices and products designed to push the boundaries of what’s possible. From cutting-edge technology to user-friendly gadgets, our dedication to delivering top-notch solutions remained steadfast. To get a clear look, here is a lineup of innovation spotlights that we want you to look back.

A. Smart Sensing

We continued to lead in sensing technologies, introducing a range of high-precision sensors and modules in 2023. In August, we announced the launch of groundbreaking card-size LoRaWAN GPS tracker SenseCAP T1000, offering a seamless indoor and outdoor tracking worldwide. We’ve also introduced the LPWAN Asset Tracker Dev Kit for Amazon Sidewalk based on our Wio Tracker 1110, designed to simplify how you build indoor and outdoor tracking solutions on the emerging Amazon Sidewalk network.
Another highlight was the launch of SenseCAP AI, our AI-powered sensor data analysis solution designed to help you make the most of your sensor data. With SenseCAP AI, you can easily analyze the data collected by your SenseCAP sensors, gain actionable insights, and optimize your operations for improved efficiency and reduced cost.

B. Edge AI

Our commitment to advancing technology was evident in the release of AIoT solutions that seamlessly integrated artificial intelligence with the Internet of Things.
The debut of the XIAO ESP32S3 Sense caused a sensation in the community, along with a series of XIAO compatible accessories such as the 24GHz mmWave Sensor for XIAO, ePaper Breakout Board, 6×10 RGB MATRIX for XIAO etc. (Explore more). Moreover, we have successfully integrated and certified the XIAO nRF52840 Module for Amazon Sidewalk, empowering developers to create their own Bluetooth LE devices with Amazon Sidewalk capabilities and exploring the vast potential of Sidewalk-enabled IoT solutions. These powerful and versatile microcontrollers set new standards for performance and functionality, empowering creators to bring their ideas to life. Click here to view the one-page XIAO Series 2023 Yearly Round-up.

We also launched an upgraded version of reTerminal, reTerminal DM, based on the great demand from our users and also our technology accumulation in the field of Raspberry Pi. Additionally, with the launch of reComputer J4012, a hand-size edge AI full system powered by NVIDIA Jetson Orin NX 16GB module, we aim to unleash advanced AI with compact space. Other upgrades on the #reThings series include reComputer Industrial J3011, reServer Industrial J4012, J401 carrier and so on. These solutions not only showcased our dedication to the latest trends but also provided users with powerful tools for intelligent and connected projects.
Step further, we introduced the SenseCraft AI, a new suite of applications including an open-source inference server and web UI to experience no-code deployment of AI models to edge devices.

C. Low-Power Network

Our product offerings catered to a diverse set of applications, fostering innovation across industries. Closely collaborating with BeagleBoard, we introduced the reCharger, a product-ready open-source EV charging solution powered by BeaglePlay and EVerest, at the Embedded Open Source Summit (EOSS) 2023.
To make technology accessible for all via a more open, interactive, and inclusive platform, we’ve released the new Seeed WiKi platform, which is the home of all our technical documentation, covering Sensor, Network, Edge, and the Cloud & Chain. It enables the whole community to get involved in contributions.

Utilizing cutting-edge technology and coordinating resources, we’re dedicated to delivering another high-quality product that our community can be proud of.

II. Embrace Communities, Co-Grow with Partners

None of our accomplishments would be possible without the unwavering support of our incredible community and partners. As we look back on 2023, we are endlessly grateful for the camaraderie, engagement, and enthusiasm. Your support is the driving force behind every innovation and success story.
In February, we upgraded to the Elite level of the NVIDIA Partner Network (NPN), the program’s highest level for companies demonstrating competency in NVIDIA embedded and edge technologies. March, Seeed collaborated with the official Raspberry Pi team to showcase the new edge device, reTerminal DM, at Embedded World 2023. Together with our Edge AI partners Lumeo, CVEDIA and Cochl, we participated in ISC West and showcased how Seeed’s NVIDIA Jetson product line series is transforming the security industry by leveraging Vision AI and Sound AI. We welcomed our new partners Isarsoft in June and N3uron in August.
Then, in September, we were honored to become the official launch partner for Home Assistant‘s new product, Home Assistant Green. We worked closely with partners Traxmate, Tago.IO, Akenza, Qubitro, Widglix to deliver live demos of full stack tracking solutions at The Things Conference 2023 featuring the SenseCAP T1000 Tracker (Explore our tracker partner ecosystem here). Later this year, we announced our partnership with Scailable, offering a streamlined approach to deploy AI models on Seeed’s edge devices, and partnered with AWS IoT team to create imersive workshops and live demos at AWS re:Invent. Throughout the year, we also work together with the LoRa Alliance and the Alliance members to participate in events of LoRaWANLive Tokyo, Smart City Expo World Congress to support the growth of the global LoRaWAN ecosystem.

We expanded our commitment to the Internet of Things with the introduction of the Co-Create Program, which helps transforms your prototype into a market-ready product, handling marketing and logistics for you. Approved prototypes are showcased on Seeed Studio’s marketplace, with creators earning a share of the sales revenue.

Seeed Studio took a significant step towards community collaborations with the initiation of the Contributors Program, a dynamic program crafted to bring makers from our community together to co-build innovative solutions, and the Ranger Program, not only to extend the reach of our technology offerings and service expertise but also to nurture a core group of experts who can become our close partners in product development and even market expansion.
Specially, as we celebrated our 15th anniversary early in June, we held story-sharing campaigns to connect with our valued community. We were amazed by the outpouring of responses we received – nearly 120 engaging stories from community members in over 40 countries and regions (Read more).

A big THANK YOU to all from the bottom of our hearts for your unwavering support!

III. Success Stories

In the canvas of innovation and technology, Seeed Studio proudly presents a spectrum of success stories that have not only embraced cutting-edge hardware but have also translated into real-world impact.

A. Environment Sensing

Rice Pest and Disease Monitoring Solution to Ensure a Bountiful Harvest

SenseCAP Devices Enabling Sophisticated Fermentation Control in Baijiu Distillery

Empowering Forest Rangers with Raspberry Pi-powered Customized HMI

Smart City: 500+ SenseCAP LoRaWAN Devices Deployed to Mitigate Urban Heat Island in Cagliari Italy

Smart Black Soldier Fly Farming in Tanzania: Using SenseCAP Sensors and Outdoor Gateway for Sustainable Livestock Feed Production!

OPEN Sustainable Agriculture Experiment with SenseCAP on Jamaica Farms

Smart Campus: Enhancing Geography Education at Hills Grammar School with SenseCAP Sensors in Australia

Micro-city Advanced Perception and Decision-making Assistance System

Bring Optics to Life, Expand Perception Network to the Microscopic Level

Smart Poultry Farm in Canada: Enhancing Production Efficiency and Animal Welfare with AIoT Technologies

Elevating Solar PV Monitoring System With Blues & Qubitro Powered By Seeed Wio-E5 Module and Fusion PCBA Service

B. Activity Management

Retail Checkout System Powered by Vision AI – No More Waiting in Long Queue

Revolutionizing Classroom Management with IoT and Raspberry Pi

Smart Transportation Utilizing 3D Scene Reconstruction to Identify Individual Distance and Number

Video Analytics Solution in Airports for Operation Efficiency Improving and Safety Enhancement

Smart Mobility Solution with Driver Behavior Detection to Reduce Road Accident Risk

A Safer Tomorrow: reRouter is Enhancing Security Monitoring Solution

Streamlining Event Photography with PhotoNodes and Seeed Studio’s reTerminal Kiosk Server

Making Neighborhoods Safer with Patrolio’s Service and Seeed reRouter

AI-Driven Video Analytics for Automotive Dealer Warehouse Security

Enhancing the Safety of the Workplace Using Raspberry Pi Powered reTerminal DM

Autonomous Shuttle Bus at University of Waterloo: AI-powered Driving Environmental and Traffic Perception

Streamlining Transportation with Jetson: Advanced Multi-category and Cross-lens Tracking for Complex Scenarios

Computer Vision with Fitness: Effectively Evaluate Human Motion with Feedback in Real-time

Computer Vision for Zoo Management: Learning from Animals’ Life Patterns to Enhance Welfare

People Flow Analysis in Public Space – Especially Avoid Missing Detection due to Occlusion

Vision AI Helps Improve Customer Satisfaction: Learn from Your Customers’ Behavior and Respond Fast

Take Timely Action with Jetson Orin NX: Dealing with Complex Traffic Control Situation

POP CAMERA Virtual Reality Kit | A Revolutionary DIY Device for Creating Immersive 360° Video Experiences Powered by Seeed Fusion PCBA and Raspberry Pi CM4

C. Equipments Upgrade

Maximizing Profits with Proper Storage Techniques in Farming with Raspberry Pi-powered reTerminal DM

Revolutionizing Smart Buildings with Raspberry Pi-powered Intelligent Control Systems

Rough Terrain Robot with Computer Vision for Harsh Environment Mapping and Heavy Transportation

Streamlining Medical Checkups Enhancing Medical Practices with Seeed’s Raspberry Pi-powered Customizable reTerminal DM

2D&3D Machine Vision for High Frame Rate Video Streaming Analytics with Depth Cameras

Automated Pizza Making System with Consistent High-Quality Food Processing and Intelligent Guidance

The Smart Food Container with Quality and Volume Monitoring with Home Assistant

Edge AI in QSRs: Enhancing Operation Efficiency and Delivering Excellent Service

Edge AI-enabled Drones Delivering First Response for Public Safety

Smart Security Sites for Community Safety Maintaining and Early Warning

Smart Building Metering Made Easy: BeagleBone® Green-based Solution for Real-time Monitoring and Optimization

Promote Circular Economy by Improving Waste Resource Traceability and Management

Empowering Efficiency: How Raspberry Pi Transforms Indoor Energy Management

Streamlining Defect Detection: Raspberry Pi Empowers Deep Learning-based Inspection Systems for Manufacturing

Raspberry Pi-enabled Innovation: Cutting-Edge Fire Detection and Prevention System Driving Extensive Industrial Applications

Discover The Stylish Flap Clock: Dr. Tõnis’ Masterpiece Energized By Seeed XIAO ESP32C3 and Fusion PCBA Service

ANAVI Launches CircuitPython-Programmable Macro Pad 12 & Arrows Mechanical Keyboards Powered by Seeed XIAO RP2040 & Seeed Fusion (Crowdfunding)

That’s all we have for this year in review!

2023 was a year of remarkable achievements for Seeed Studio. Through cutting-edge hardware, integrated software platforms, meaningful partnerships, and the continuous success of our community, we’ve solidified our commitment to fostering innovation and empowering creators worldwide. As we look ahead, the momentum gained in 2023 serves as a foundation for even greater accomplishments in the coming years. Here’s to a future filled with innovation, collaboration, and the boundless possibilities that technology brings.

As always, we can’t wait to see what you make. Shoot us a tweet @seeedstudio, or let us know on LinkedIn, Discord, or publish your project on our Project Hub on Hackster. Please be safe out there, be kind to one another, and we’ll see you next month with even more exciting news!

The post Year in Review: Seeed Studio in 2023 — A Symphony of Innovation, Growth and Unforgettable Moments! appeared first on Latest Open Tech From Seeed.

Improving the Efficiency of Logistics Dispatch for Huge Storage

Jennie Wang — Sun, 31 Dec 2023 14:57:14 +0000

Hardware: reComputer J1020v2 with NVIDIA Jetson Nano

Application: Goods Detection

Industry: Logistics Management

Deployment Location: United States

The efficiency of transporting goods from loading docks to retail warehouses could be one of the most crucial parts to see if the companies can optimize logistics management. For example, achieving the digital transformation of the supply chain means not immediately dispatching materials upon availability but rather shipping them only when vehicles reach 100% capacity, thus reducing costs and balancing inventory.

Challenge

While this concept seems straightforward in theory, implementation might be challenging, which requires continuous human monitoring of available space in containers and delivery trucks. Relevant information must be effectively communicated to transportation and operations managers, and may also accompanied by human inspection errors and existing bias based on previous human experiences. Nowadays, human resources can benefit from IoT technology, supported by the integration of computer vision with supply chain management on the edge.

Solution

In these checkpoint operations, Edge AI, trained to detect available space, revolutionizes the process. Visual AI uses existing cameras to identify reference points in images, combining with Jetson Nnano for fast processing and inferencing to assess space utilization in specific containers, and report these findings to logistics managers. Combined with serial number tracking, operations personnel can swiftly determine the available capacity of their fleet.

Moreover, computer vision systems can identify the volume characteristics of goods and aid in determining pallet dimensions. These solutions, by measuring the physical attributes of goods and packaging in the manufacturing and distribution chain, optimize operational efficiency.

Formerly reliant on specialized scanning equipment, modern AI now utilizes standard cameras to detect items’ dimensions, reducing implementation costs and streamlining integration. The true logistics capability lies in seamlessly integrating this data with transportation capacity information to maximize the number of products loaded into containers.

Seeed NVIDIA Jetson Ecosystem

Discover infinite computer vision application possibilities through our vision AI resource hub!

Take the first step and send us an email at edgeai@seeed.cc to become a part of this exciting journey!

The post Improving the Efficiency of Logistics Dispatch for Huge Storage appeared first on Latest Open Tech From Seeed.

Latest Open Tech From Seeed

【Exciting 2024 Kickoff Offer🤩】Up to 99 Pcs! Enjoy FREE Assembly for Your First PCBA Order!

Scale up Your Creation With Seeed Studio Fusion

Seeed Studio Accelerates Vision AI and Generative AI at the Industrial Edge with NVIDIA

Seeed NVIDIA Jetson Ecosystem

4 Most Promising LPWAN Connectivity: A Comprehensive Comparison of LoRaWAN, Amazon Sidewalk, Helium, and Cat-M,

Table of Contents

What is LPWAN?

LoRaWAN: The Open Standard for Global IoT

LoRaWAN Pros & Cons

Applications of LoRaWAN

LoRaWAN Products Recommendation

Amazon Sidewalk: Bridging the Gaps in Urban Connectivity

Sidewalk Pros & Cons

Sidewalk Applications

Sidewalk Compatible Products Recommendation

Helium: Decentralized LPWAN Network

Helium vs Traditional LoRaWAN

Helium Pros & Cons

Typical Applications of Helium

Helium Compatible Products

Cat-M: Low-Power Cellular Connectivity for IoT

Cat-M Pros & Cons

Cat-M Applications

Head-to-Head Comparison

The Future of LPWAN Technologies

Conclusion

LPWAN Frequently Asked Questions

Chaihuo Makerspace Joins Fab Academy as a 2024 Node!

Announcing the Champions of the OpenCV AI Competition 2023

Unleash the potential for Raspberry Pi Edge Devices with OpenCV

Dive Deep into Vision AI and Kickstart Your Next AI Application

Introducing Maker Camp in Shenzhen

What's in the Mix?

What Seeed Offers

Sharing is Caring!

How to Participate?

Guidelines for Content Organization and Contribution

Webinar: Leveraging LoRaWAN in Tracking Solutions for Healthcare

Speakers:

Webinar Details:

Generative AI at the Edge Fundamentals: What is it and how it works?

What is Generative AI？

Generative AI Architecture Underneath

Transformer

Foundation Model

Generative AI Model Types

Text-to-Text

Text-to-Image

Text-to-Task

What’s Next? Ready for Practical Applications?

Free Trail Virtually for NVIDIA Jetson AGX Orin Developer Kit!

Seeed: NVIDIA Jetson Ecosystem Partner

Pose Landmark Detection on Raspberry Pi-powered HMIs at the Edge

Introduction

Why perform pose landmarks detection at the Edge?

Deploy in Raspberry Pi-powered Seeed Studio’s Solutions

Applications of Pose Landmarks detections

Seeed Studio’s Raspberry Pi Ecosystem

More Resources

Edge-Enhanced Face Detection: A Deep Dive with Raspberry Pi-Powered Devices

Introduction

Why Face detection at Edge is important?

What are the applications of Face Detection?

Security and Surveillance

Retail Analytics

Seeed Studio’s Raspberry Pi Ecosystem

More Resources

Year in Review: Seeed Studio in 2023 — A Symphony of Innovation, Growth and Unforgettable Moments!

Long Blog Alert: A Patient Read Ahead

I. Infinite Innovation: New Products and Technologies

A. Smart Sensing

B. Edge AI

C. Low-Power Network

II. Embrace Communities, Co-Grow with Partners

III. Success Stories

A. Environment Sensing

Rice Pest and Disease Monitoring Solution to Ensure a Bountiful Harvest

SenseCAP Devices Enabling Sophisticated Fermentation Control in Baijiu Distillery

Empowering Forest Rangers with Raspberry Pi-powered Customized HMI