Engineer and YouTuber Carl Bugeja recently developed CodeCell, a tiny ESP32-C3 development board designed as the brain for robots, wearables, and smart home devices. This module features a nine-axis inertial measurement unit (IMU) for motion fusion and an optional VCNL4040 light sensor. It includes a USB Type-C port for data and power as well as a lithium-polymer battery with a charging circuit. Measuring just 18.5 x 18.5mm this compact board is even smaller than other tiny ESP32 development boards such as Waveshare’s ESP32-S3-Zero and Seeed Studio’s XIAO ESP32S3. However, the Epi C3 is smaller at 23 x 12.75 mm, and so are the Unexpected Maker NANOS3 (25 x 10 mm) and Unexpected Maker OMGS3 (28 x 11 mm). CodeCel ESP32-C3 mini development board specification Microcontroller – ESP32-C3 RISC-V MCU 160MHz 32-bit RISC-V processor core 400kB SRAM, 4MB flash storage Wi-Fi 4 and Bluetooth Low Energy (BLE) connectivity Sensors Vishay VCNL4040 light [...]
Renesas has recently introduced the CCE4511 four-channel IO-Link master IC and the ZSSC3286 IO-Link-ready dual-channel sensor signal conditioner IC along with their development boards designed for harsh industrial environments. The CCE4511 master IC supports four channels with 500mA driving current, overvoltage detection, and overcurrent protection, Additionally, it has an integrated IO-Link Frame Handler that reduces microcontroller load. The ZSSC3286on is the first sensor signal conditioner with an integrated IO-Link compliant stack, meaning you don’t need a separate microcontroller for signal handling. Additionally, it features 24-bit ADCs and advanced diagnostic functions for advanced tasks. Both products are optimized for industrial automation, offering energy efficiency, smaller PCB sizes, and robust system diagnostics. CCE4511 IO-Link master and ZSSC3286 sensor signal conditioner IC Specifications CCE4511 IO-Link master Main Chip – CCE4511 4-Channel IO-Link Master PHY with integrated Frame Handler Number of Channels – 4 IO-Link master channels Frame Handler – Hardware frame handler for [...]
With industries increasingly adopting LoRaWAN and MQTT protocols, Seeed Studio’s devices—like the SenseCAP LoRaWAN sensors and gateways—are now fully supported on Blynk’s platform. This expanded functionality simplifies IoT deployments by allowing users to monitor and control their devices through Blynk‘s intuitive dashboard, without needing extensive coding or infrastructure setup.
“The expanded functionality available with Blynk’s platform is a game-changer for businesses using Seeed Studio SenseCAP LoRaWAN devices,” said Joey Jiang, VP of Industrial Application Group at Seeed Studio. “Our customers can now take advantage of Blynk’s advanced device management features, such as multi-level user management and granular access controls, to manage fleets of devices at scale with ease. This integration allows businesses to focus on their operations while Blynk and Seeed handle the heavy lifting on the backend, from device provisioning to user control.”
Empowering Developers and Businesses with No-Code IoT Solutions
Through Blynk’s intuitive no-code platform, users gain access to advanced device management tools such as visual data visualization, automation workflows, and real-time alerts. With native MQTT support and a recent integration with The Things Stack for LoRaWAN, Seeed Studio hardware can now unlock unprecedented possibilities for IoT deployments.
“Our mission has always been to simplify IoT for businesses of all sizes,” said Pavel Bayborodin, CEO of Blynk. “By expanding our platform to support industry-standard protocols like LoRaWAN and MQTT, and partnering with Seeed Studio’s robust hardware lineup, we are enabling companies to launch powerful IoT systems faster than ever.”
Unlocking Opportunities Across Smart Industries
The extended partnership offers tremendous opportunities across key industries like smart agriculture, industrial automation, and smart cities. With Seeed’s SenseCAP LoRaWAN devices integrated into Blynk, businesses can achieve remote monitoring, real-time data transfer, and centralized device management with minimal effort. Whether deploying sensors in the field or managing urban infrastructure, users benefit from both Blynk’s software capabilities and Seeed’s reliable hardware for cost-effective solutions.
Discover Seeed Studio Products with LoRaWAN and MQTT Support
Explore Seeed Studio’s wide range of IoT solutions designed to seamlessly integrate with Blynk’s platform. Whether you need SenseCAP LoRaWAN sensors for environmental monitoring, LoRaWAN gateways for reliable connectivity, or development kits for rapid prototyping, Seeed Studio has the tools to bring your IoT vision to life.
Seeed Studio, founded in 2008, is a pioneer in Open Hardware and IoT innovation, offering a broad portfolio of industrial IoT solutions, including sensor modules, edge devices, and platforms like SenseCAP. By promoting collaborative development and open-source principles, Seeed Studio empowers developers and enterprises worldwide to design solutions that address local challenges and advance emerging technologies such as AI and IoT.
About Blynk
Blynk is a leading low-code IoT platform that enables businesses to build custom mobile IoT applications and manage millions of connected devices globally. Used by over 1 million developers and 5,000 businesses, Blynk simplifies IoT management through easy-to-use dashboards and advanced user management features, accelerating time to market and helping companies scale their connected products.
Millimeter Wave (mmWave) radar technology, recognized for its high accuracy, privacy-centric capabilities, adaptability, and flexibility, is increasingly becoming a critical tool in privacy-oriented sensing applications. These applications range from presence and fall detection to sensitive monitoring of breathing and heartbeat.
To empower developers worldwide to adapt mmWave radar for more responsive automation, we are now excited to introduce two new mmWave Sensor Kits designed to meet diverse needs:
Priced at $24.9, both kits utilize the same hardware platform but are equipped with specialized pre-set algorithms tailored for distinct motion detection tasks—fall detection and breathing & heartbeat monitoring, respectively.
Key Features of the New mmWave Sensor Kits
These kits leverage 60GHz mmWave technology to offer reliable detection capabilities:
Presence and Fall Detection: Detects subtle motions, accurately identifying human activities such as standing, walking, or falling.
Presence, Breathing and Heartbeat Monitoring: Captures minute displacements caused by heartbeat and chest movements, providing invaluable data for health monitoring.
Each kit features a mmWave Sensor Module with:
Light Level Sensing
Customizable WS2812B RGB LED
Support for Extended Grove Sensors/Actuators
Powered by the XIAO ESP32C6, these kits come with pre-flashed ESPHome firmware and support multiple wireless protocols, including Wi-Fi, Bluetooth Low Energy (BLE), Zigbee, and Thread. They are designed for easy no-code integration with Home Assistant via ESPHome, allowing users to customize detection zones and analytics. P.S. A 3D printing enclosure file is available for free download as a reference design to fit in your application.
Why Choose mmWave Sensors for Your Projects?
High Resolution and Accuracy: Essential for applications requiring precise detection and differentiation of human movements.
Non-contact and Non-invasive: Ideal for continuous monitoring without disturbance, crucial for healthcare and home environments.
Operational in Various Conditions: Functions effectively regardless of lighting conditions or physical barriers.
Privacy Preservation: Does not capture identifiable images or videos, ensuring privacy while monitoring.
Real-Time Processing: Supports immediate data processing for quick responses to detected emergencies.
Flexible Integration and Wide Coverage: Easily integrated into existing systems, enhancing capabilities without significant modifications.
Expanding Your Toolkit
If you’re a long-term supporter of Seeed, you’re likely familiar with our mmWave Sensor Series. We have prepared a comparison guide to help you select the best mmWave sensors for your projects.
Reserve your mmWave Sensor Kit today and enhance your automation systems, whether for smart homes, healthcare, safety monitoring, elderly caring, security, or caregiving.
Hey community, we’re curating a monthly newsletter centering around the beloved Seeed Studio XIAO. If you want to stay up-to-date with:
Cool Projects from the Community to get inspiration and tutorials Product Updates: firmware update, new product spoiler Wiki Updates: new wikis + wiki contribution News: events, contests, and other community stuff
With the introduction of Home Assistant hub, setting up smart home automation has become more accessible than ever. Selecting the right sensors is essential to collect accurate data and automate various home systems.
This guide explores sensor types compatible with Home Assistant hub, offering automation ideas and real-world use cases. We’ll also cover how to integrate these sensors with Home Assistant hub, ensuring seamless operation whether through native support or additional setup with ESPHome.
Table of Contents
1. Temperature and Humidity Sensors
Monitoring temperature and humidity helps you automate climate control systems, ensuring your home stays comfortable and energy-efficient. Here are some top picks that work well with Home Assistant hub:
This sensor provides accurate readings of temperature and humidity, useful for automating HVAC systems or dehumidifiers. While not natively supported, it can be integrated with Home Assistant using ESPHome via I2C.
A more budget-friendly sensor for temperature and humidity. Although basic, it serves well for simple climate monitoring in home spaces, integrated via ESPHome.
Perfect for harsher environments such as basements or garages. Integration is similar to the DHT20 and requires using ESPHome or MQTT for Home Assistant compatibility.
A more precise option for environments that require long-term stability. Similar ESPHome setup required for Home Assistant integration.Use case: Set up an automation to turn on a dehumidifier when the humidity level rises above 65%, preventing mold in damp areas.
This sensor not only measures temperature and humidity but also tracks air quality metrics, providing a holistic view of your environment. It integrates with Home Assistant using ESPHome.
Use case example: Set up an automation to turn on a dehumidifier when the humidity level rises above 65%, helping to prevent mold growth in damp areas like basements or bathrooms. Alternatively, create an automation that adjusts your HVAC system to maintain optimal indoor temperature throughout the day.
2. Air Quality Sensors
Good indoor air quality is essential, especially for homes with allergies or asthma. These sensors help you automate air purifiers or ventilation systems based on real-time data:
A great solution for general air quality monitoring in home spaces. It tracks VOCs and dust particles, providing vital information for automating air purifiers.
This sensor measures CO2, temperature, and humidity, making it ideal for offices or classrooms. You can set it up with ESPHome for Home Assistant automation.
Use case example: Automate your air purifier to activate when air quality falls below a specific threshold, such as when VOC levels exceed safe limits or PM2.5 dust particles are detected. This can help maintain clean air inside your home, especially during high-pollution periods.
3. Motion and Presence Sensors
Detecting movement can enhance your home security and automate lights or other devices based on activity:
A highly accurate sensor for presence detection. Works seamlessly with Home Assistant using ESPHome for automating lights or appliances based on human presence.
Fully Zigbee compatible, this sensor works natively with Home Assistant, perfect for automating lights or cameras upon motion detection.
Use case example: Automate hallway or room lights to turn on when the motion sensor detects movement and turn off after a set period of inactivity. This saves energy while adding convenience. You can also use the sensors to trigger security cameras when unexpected motion is detected.
4. Water and Soil Sensors
These sensors help with garden care or detecting potential water leaks:
A more advanced soil moisture sensor, also ESPHome-compatible, to optimize garden or greenhouse watering.
Use case example: Automate your irrigation system to activate when the soil moisture drops below a certain threshold, ensuring your garden or indoor plants receive water at the right time. You can also set up notifications to remind you when it’s time to water your plants manually.
5. Door and Window Sensors
Enhance home security with automation that triggers alerts or actions when doors or windows open:
Another Zigbee option, seamlessly integrates with Home Assistant for reliable door and window status monitoring.
Use case example: Create an automation where your porch light turns on when the front door is opened at night, or trigger an alarm if a window is opened when you’re away from home. You can also receive a notification on your phone if any door or window is left open for too long.
6. Light Sensors
Control indoor lighting based on ambient light conditions:
Similar to the Light Sensor v1.2 but offers more detailed ambient light data for use in advanced smart lighting automations via ESPHome.Use case: Automate living room lights to adjust based on natural light conditions, ensuring a comfortable environment while saving energy.
Use case example: Automate your indoor lighting to adjust based on the amount of natural light entering the room. For example, you can dim your living room lights as the sun sets, creating a comfortable atmosphere while reducing energy consumption.
These displays allow for real-time visualizations of environmental data. You can link them to Home Assistant through ESPHome for a detailed display of home sensor information.
Conclusion
Integrating the right sensors with the Home Assistant hub enhances your home’s automation potential.
Sonoff Zigbee sensors are natively compatible, while Grove and mmWave sensors require additional setup through ESPHome.
Whether you’re looking to monitor air quality, automate lighting, or manage soil moisture, these sensors provide powerful solutions for elevating your smart home experience.
Authored by Mengdu and published on Hackster, for sharing purposes only.
AI gadgets Rabbit R1 & SenseCAP Watcher design, UI, user experience compared – hardware/interaction highlights, no application details.
Story
The world of AI gadgets is rapidly evolving, with companies racing to deliver intelligent home companions. Two such devices, the Rabbit R1, and SenseCAP Watcher, recently caught my attention through very different means – brilliant marketing drew me to purchase the former, while the latter was a review unit touted as a “Physical AI Agent” by Seeed Studio.
Intrigued by the potential convergence between these products, I embarked on an immersive user experience testing them side-by-side. This review offers a candid assessment of their design, user interfaces, and core interactions. However, I’ll steer clear of Rabbit’s app ecosystem and third-party software integration capabilities, as Watcher lacks such functionality by design.
My goal is to unravel the unique propositions each gadget brings to the AI gadgets market and uncover any surprising distinctions or similarities. Join me as I separate gimmick from innovation in this emerging product category.
Packaging
Rabbit really went all out with the packaging for the R1. As soon as I got the box, I could tell this wasn’t your average gadget. Instead of cheap plastic, the R1 comes cocooned in a crystal-clear acrylic case. It looks and feels incredibly premium.
It allows you to fully admire the R1’s design and interactive components like the scroll wheel and speakers before even taking it out. Little etched icons map out exactly what each part does.
The acrylic case doesn’t just protect – it also doubles as a display stand for the R1. There’s a molded pedestal that cradles the plastic body, letting you showcase the device like a museum piece.
By the time I finally got the R1 out of its clear jewel case, I was already grinning like a kid on Christmas day. The whole unboxing makes you feel like you’re uncovering a precious gadget treasure.
While the Watcher is priced nearly half that of the Rabbit R1, its eco-friendly cardboard packaging is anything but cheap. Extracting the Watcher unit itself is a simple matter of gently lifting it from the integrated enclosure.
At first glance, like me, you may puzzle over the purpose of the various cutouts, folds, and perforations. But a quick peek at their wiki reveals this unassuming exterior actually transforms into a multi-functional stand!
Echoing the form of a desktop calendar, a central cutout cradles the Watcher body, allowing it to be displayed front-and-center on your desk like a compact objet d’art. A clever and well-considered bit of innovation that deserves kudos for the design team!
Interaction Logic
Despite being equipped with speakers, microphone, camera, scroll wheel, and a touchscreen display – the R1 restricts touch input functionality. The touchscreen remains unresponsive to touch for general commands and controls, only allowing input through an on-screen virtual keyboard in specific scenarios like entering a WiFi password or using the terminal interface.
The primary interaction method is strictly voice-driven, which feels counterintuitive given the prominent touchscreen hardware. It’s puzzling why Rabbit’s design team limited core touch functionality on the included touchscreen display.
The overall operation logic also takes some getting used to. Take the side button dubbed the “PTT” – its function varies situationally.
This unintuitive behavior tripped me up when configuring WiFi. After tapping “connect”, I instinctively tried hitting PTT again to go back, only to accidentally cancel the connection instead. It wasn’t until later that I realized using the scroll wheel to navigate to the very top option, then pressing PTT is the correct “back” gesture.
While not necessarily a flaw, this interaction model defies typical user expectations. Most would assume a core navigation function like “back” to be clearly visible and accessible without obscure gestures. Having to precisely scroll to the top option every single time just to return to the previous menu is quite cumbersome, especially for nested settings trees.
This jarring lack of consistency in the control scheme is truly baffling. The operation logic appears haphazardly scattered across different button combinations and gestures depending on the context. Mastering the R1’s controls feels like an exercise in memorizing arbitrary rules rather than intuitive design principles.
In contrast to the Rabbit R1, the Watcher device seems to have a much simpler and more consistent interaction model. This could be attributed to the fact that the Watcher’s operations are inherently not overly complex, and it relies on a companion smartphone app for assistance in many scenarios.
Like the R1, the Watcher is equipped with a scroll wheel, camera, touchscreen, microphone, and speakers. Additionally, it has various pin interfaces for connecting external sensors, which may appeal to developers looking to tinker.
Commendably, the current version of the Watcher maintains a high degree of unity in its operational logic. Pressing the scroll wheel confirms a selection, scrolling up or down moves the cursor accordingly, and a long press initiates voice interaction with the device. This level of consistency is praiseworthy.
Moreover, the touchscreen is fully functional, allowing for a seamless experience where users can choose to navigate via either the scroll wheel or touch input, maintaining interactivity consistency while providing independent input methods. This versatility is a welcome design choice.
However, one minor drawback is that the interactions lack the “stickiness” found in smartphone interfaces. Both the scroll wheel and touch inputs exhibit a degree of frame drops and latency, which may be a common limitation of microcontroller-based device interactions.
When I mentioned that “it relies on a companion smartphone app for assistance in many scenarios, ” I was referring to the inability to perform tasks like entering long texts, such as WiFi passwords, directly on the Watcher‘s small screen. This reliance is somewhat unfortunate.
However, given the Watcher’s intended positioning as a device meant to be installed in a fixed location, perhaps mounted on a wall, it is understandable that users may not always need to operate it directly. The design team likely factored in the convenience of using a smartphone app for certain operations, as you wouldn’t necessarily be handling the Watcher itself at all times.
What can they do?
At its core, the Rabbit R1 leverages cloud-based large language models and computer vision AI to provide natural language processing, speech recognition, image identification and generation, and more. It has an array of sensors including cameras, microphones and environmental detection to take in multimodal inputs.
One of the Rabbit R1’s marquee features is voice search and question answering. Simply press the push-to-talk button and ask it anything, like “What were last night’s NBA scores?” or “What’s the latest on the TikTok ban?”. The AI will quickly find and recite relevant, up-to-date information drawn from the internet.
The SenseCAP Watcher, while also employing voice interaction and large language models, takes a slightly different approach. By long-pressing the scroll wheel on the top right of the Watcher, you can ask it profound existential questions like “Can you tell me why I was born into this world? What is my value to the universe?” It will patiently provide some insightful, if ambiguous, answers.
However, the key difference lies in contextual awareness: unlike the Rabbit R1, the Watcher can’t incorporate your current time and location into its responses. So while both devices might ponder the meaning of life with you, only the Rabbit R1 could tell you where to find the nearest open café to continue your existential crisis over a cup of coffee.
While both devices offer voice interaction capabilities, their approaches to visual processing showcase even more distinct differences.
Vision mode allows the Rabbit R1’s built-in camera to identify objects you point it towards. I found it was generally accurate at recognizing things like office supplies, food, and electronics – though it did mistake my iPhone 16 Pro Max for older models a couple times. This feature essentially turns the Rabbit R1 into a pocket-sized seeing-eye dog, ready to describe the world around you at a moment’s notice.
Unlike the Rabbit R1’s general-purpose object recognition, the Watcher’s visual capabilities appear to be tailored for a specific task. It’s not designed to be your all-seeing companion, identifying everything from your morning bagel to your office stapler.
Things are starting to get interesting. Seeed Studio calls the SenseCAP Watcher a “Physical AI Agent” – a term that initially puzzled me.
The term “Physical” refers to its tangible presence in the real world, acting as a bridge between our physical environment and Large Language Model.
As a parent of a mischievous toddler, my little one has a habit of running off naked while I’m tidying up the bathroom, often resulting in them catching a chill. I set up a simple task for the Watcher: “Alert me if my child leaves the bathroom without clothes on.” Now, the device uses its AI to recognize my child, determine if they’re dressed, and notify me immediately if they attempt to make a nude escape.
Unlike traditional cameras or smart devices, the Watcher doesn’t merely capture images or respond to voice commands. Its sophisticated AI allows it to analyze and interpret its surroundings, understanding not just what objects are present, but also the context and activities taking place.
I’ve experienced its autonomous capabilities firsthand as a working parent with a hectic schedule. After a long day at the office and tending to my kids, I usually collapse on the couch late at night for some much-needed TV time. However, I often doze off, leaving the TV and lights on all night, much to my wife’s annoyance the next morning.
Enter the Watcher. I’ve set it up to monitor my situation during late-night TV watching. Using its advanced AI, the Watcher can detect when I’ve fallen asleep on the couch. Once it recognizes that I’m no longer awake, it springs into action. Through its integration with my Home Assistant system, the Watcher triggers a series of automated actions: the TV switches off, the living room lights dim and then turn off, and the air conditioning adjusts to a comfortable sleeping temperature.
The “Agent” aspect of the Watcher emphasizes its role as an autonomous assistant. Users can assign tasks to the device, which then operates independently to achieve those goals. This might involve interacting with other smart devices, making decisions based on observed conditions, or providing insights without constant human input. It offers a new level of environmental awareness and task execution, potentially changing how we interact with AI in our daily lives.
You might think that devices like the Rabbit R1 could perform similar tasks. However, you’ll quickly realize that the Watcher’s capabilities are the result of Seeed Studio’s dedicated efforts to optimize large language models specifically for this purpose.
When it comes to analyzing object behaviors, the Rabbit R1 often provides ambiguous answers. For instance, it might suggest that a person “could be smoking” or “might be sleeping.” This ambiguity directly affects their ability to make decisive actions. This is probably a common problem with all devices using AI at the moment, too much nonsense and indecision. We sometimes find them cumbersome, often because they can’t be as decisive as humans.
I think I can now understand all the reasons why Seeed Studio calls it Physical AI Agent. I can use it in many of my scenarios. It could detect if your kid has an accident and wets the bed, then alert you. If it sees your pet causing mischief, it can recognize the bad behavior and give you a heads up.
If a package arrives at your door, the Watcher can identify it’s a delivery and let you know, rather than just sitting there unknowingly. It’s an always-vigilant smart camera that processes what it sees almost like having another set of eyes monitoring your home or office.
As for their distinct focus areas, the ambition on the Rabbit R1 side is to completely replace traditional smartphones by doing everything via voice control. Their wildest dream is that even if you metaphorically chopped off both your hands, you could just tell the R1 “I want to order food delivery” and it would magically handle the entire process from ordering to payment to confirming arrival – all without you having to lift a finger.
Instead of overcomplicating it with technical jargon about sensors and AI models, the key is that the Watcher has enough awareness to comprehend events unfolding in the physical world around it and keep you informed, no fiddling required on your end.
Perhaps this duality of being an intelligent aide with a tangible physical embodiment is the core reason why Seeed Studio dubs the Watcher a “Physical AI Agent.” Unlike disembodied virtual assistants residing in the cloud, the Watcher has a real-world presence – acting as an ever-present bridge that allows advanced AI language models to directly interface with and augment our lived physical experiences. It’s an attentive, thoughtful companion truly grounded in our reality.
Concluding
The Rabbit R1 and SenseCAP Watcher both utilize large language models combined with image analysis, representing innovative ways to bring advanced AI into physical devices. However, their application goals differ significantly.
The Watcher, as a Physical AI Agent, focuses on specific scenarios within our living spaces. It continuously observes and interprets its environment, making decisions and taking actions to assist users in their daily lives. By integrating with smart home systems, it can perform tasks autonomously, effectively replacing repetitive human labor in defined contexts.
Rabbit R1, on the other hand, aims to revolutionize mobile computing. Its goal is to replace traditional smartphones by offering a voice-driven interface that can interact with various digital services and apps. It seeks to simplify and streamline how we engage with technology on the go.
Both devices represent early steps towards a future where AI is more deeply integrated into our daily lives. The Watcher showcases how AI can actively participate in our physical spaces, while the R1 demonstrates AI’s potential to transform our digital interactions. As pioneering products, they offer glimpses into different facets of our AI-enhanced future, inviting us to imagine a world where artificial intelligence seamlessly blends with both our physical and digital realities.
There is no clear “winner” here.
Regardless of how successful these first iterations prove to be, Rabbit and Seeed Studio have staked unique perspectives on unleashing productivity gains from large language AI. Their distinct offerings are pioneering explorations that will undoubtedly hold a place in the historical arc of ambient AI development.
If given the opportunity to experience them first-hand, I wholeheartedly recommend picking up both devices. While imperfect, they provide an enthralling glimpse into the future – where artificial intelligence transcends virtual assistants confined to the cloud, and starts manifesting true cognition of our physical spaces and daily lives through thoughtful hardware/software synergies.
SparkFun has released a new air quality multi-sensor board, the Indoor Air Quality Combo Sensor, which integrates the SCD41 and SEN55 sensors from Sensirion for measuring carbon dioxide, volatile organic compounds (VOCs), particulate matter, relative humidity, and temperature. The air quality multi-sensor board simplifies power management for the two sensors via onboard DC voltage conversion and allows a single Qwiic connection for power and communication. It features two Qwiic connectors and a 0.1”-space through-hole header for I2C and power. The board is not a complete solution for indoor air quality monitoring. It has to be connected to a Qwiic-enabled microcontroller such as SparkFun Thing Plus Matter, DataLogger IoT, and the ESP32 Qwiic Pro Mini. Users can install the required Arduino libraries — the Arduino Core library, Sensirion I2C SEN5x, and SparkFun SCD4x — either via the Arduino library manager or directly from SparkFun. The device is open-source, with hardware files, [...]