# Sensor Published articles for Sensor. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Alif Semi Balletto B1 and Ensemble E1C StartKits feature Cortex-M55 + Ethos-U55 MCU for IoT and Edge AI DevFeed: [Alif Semi Balletto B1 and Ensemble E1C StartKits feature Cortex-M55 + Ethos-U55 MCU for IoT and Edge AI]() Original publisher: [Read original article]() Author: Debashis Das Published: 2026-09-15T09:00:06Z Content type: news Language: en Sources: [CNX Software - Embedded Systems News]() Topics: [Microcontrollers](), [Embedded Systems](), [Microcontroller](), [cpu](), [Internet of things](), [Artificial Intelligence](), [SDK]() Tags: [802-15-4](), [ai](), [alif](), [ble](), [camera](), [core](), [debugger](), [development-board](), [devkit](), [edge](), [edge-ai](), [embedded-systems](), [hardware](), [i2c](), [iot](), [led](), [low-power](), [mcu](), [microcontrollers](), [mikrobus](), [open-source](), [sensor](), [specifications](), [testing](), [zephyr](), [zephyr-os]() ### AI overview Alif Semiconductor's Balletto B1 and Ensemble E1C StartKits are low-cost development boards built around Cortex-M55 microcontrollers with Ethos-U55 NPUs. The Balletto B1 adds BLE 5.3 and 802.15.4 connectivity, while both boards include camera, audio, sensor expansion, debugging, and power-measurement features. ### Source excerpt Alif Semiconductor's Ensemble E1C (SK-E1C) and Balletto B1 (SK-B1) StartKits are low-cost development boards built around the company's Cortex-M55 + Ethos-U55 microcontrollers. The Balletto B1 adds BLE 5.3 and 802.15.4 wireless connectivity, while the Ensemble E1C does not have built-in wireless connectivity. Both StartKits feature a microcontroller with a 160MHz Cortex-M55 CPU, an Ethos-U55 NPU, 2MB SRAM, and 1.8/1.9MB NVM. They also include an Arducam camera header, a mikroBUS Click Board expansion socket, and two PDM microphones for camera, audio, and sensor-based projects. The Balletto B1 additionally provides the complete RF path to a chip antenna for its wireless subsystem, while both boards feature an on-board Segger J-Link debugger for development and testing. Alif Semiconductor StartKit (SK-B1 and SK-E1C) specifications: MCU SK-E1C - Alif Semiconductor Ensemble E1C SK-B1 - Alif Semiconductor Balletto B1 CPU - Arm Cortex-M55 core with Helium-M Vector Extension @ up to 160 MHz NPU - Arm [...] The post Alif Semi Balletto B1 and Ensemble E1C StartKits feature Cortex-M55 + Ethos-U55 MCU for IoT and Edge AI appeared first on CNX Software - Embedded Systems News. ## Building smarter AMRs with the Arduino® VENTUNO™ Q board DevFeed: [Building smarter AMRs with the Arduino® VENTUNO™ Q board]() Original publisher: [Read original article]() Author: Arduino Team Published: 2026-09-11T11:10:16Z Content type: article Language: en Sources: [Arduino Blog]() Topics: [Arduino](), [Physical AI](), [Microcontroller](), [Linux](), [Computer vision](), [real-time](), [systems]() Tags: [amr](), [arduino](), [autonomous-mobile-robots](), [computer-vision](), [featured](), [linux](), [mcu](), [physical-ai](), [real-time](), [robotics](), [robots](), [ros](), [sensor](), [sensors](), [ventuno-q]() ### AI overview The article explains how Arduino's VENTUNO Q board could support autonomous mobile robots by combining a Linux-capable MPU with a real-time MCU. The MPU can run Linux, ROS 2, navigation, computer vision, and AI workloads, while the MCU handles motor control, encoder feedback, inertial measurements, local sensing, and motor-driver communication. ### Source excerpt Physical AI is based on the idea that intelligence shouldn't stop at perception: instead, it should bring to life systems able to sense their environment, reason about it, and act on it - all in one continuous loop. It's what makes the difference between a device that observes and one that acts. Autonomous mobile robots [...] The post Building smarter AMRs with the Arduino® VENTUNO™ Q board appeared first on Arduino Blog. ## Home Hardware, Part 1: My Control4 Revenge Arc DevFeed: [Home Hardware, Part 1: My Control4 Revenge Arc]() Original publisher: [Read original article]() Published: 2026-09-08T00:34:58Z Content type: opinion Language: en Sources: [Jessie Frazelle]() Topics: [Home Assistant](), [Hardware](), [Bluetooth](), [Homekit](), [codex]() Tags: [api](), [bluetooth](), [codex](), [connect](), [hardware](), [home-assistant](), [homekit](), [sensor](), [sensors]() ### AI overview The author describes designing consumer hardware for a Home Assistant-based smart home, including a Bluetooth sensor hub and a maintenance display. The post discusses Bluetooth proxy range, regulatory constraints, testing considerations, and the use of NFC stickers for maintenance tracking, while reflecting on using Codex during the project. ### Source excerpt Fuck1 it, we're doing consumer hardware for ourselves now and getting fucked by economies of scale, I guess. This all started with me buying some Olimex Bluetooth proxies for Home Assistant. Then I started looking at the components and wondering if I could get better range. Now I'm designing boards, displays, and enclosures, and emailing manufacturers because their bezels are enormous. I've ordered the first two boards: a Bluetooth sensor hub and a little maintenance display. I've been working on this in Codex, and this post is going to go through what it was good at, where it got stuck or got things wrong, and where I had to step in. Why build this? Honestly, Control4, Savant, and the rest of these fucking systems seem built for rich people who don't know how to turn on their TV and would rather call someone. I want to program the fucking thing. Control4 puts HomeKit integration in its paid Connect tier.2 Why am I paying a recurring fee to connect things I already bought? I don't want to call a Control4 or Savant dealer, either, just because I want to change how something works. Give me API access or give me death. Source works too. I'll pick the hardware and connect it to Home Assistant, HomeKit, or my own code. If I want another sensor or some weird maintenance reminder, I can write that. It's my fucking house.31 Back to the Bluetooth proxies With a Bluetooth proxy, I can put the BLE radio near the sensors and get back to Home Assistant over the network.4 The machine running Home Assistant doesn't have to be within range of every sensor. When I mentioned my plans to Paul (paultag) over Slack, he pointed out that Olimex might be constrained by what the FCC allows, not just the components it picked. A radio supporting more transmit power doesn't mean you can use all of it.5 I hadn't thought about that. These are boards for my house. I'm not selling them. Fuck it, I'll build them and test them. I still have to measure the range; a bigger number on the radio's datash ## D-Robotics RDK S100P - A 128 TOPS alternative to NVIDIA Jetson Orin NX 16GB with Cortex-A78AE/R52+ cores DevFeed: [D-Robotics RDK S100P - A 128 TOPS alternative to NVIDIA Jetson Orin NX 16GB with Cortex-A78AE/R52+ cores]() Original publisher: [Read original article]() Author: Debashis Das Published: 2026-08-31T08:06:13Z Content type: news Language: en Sources: [CNX Software - Embedded Systems News]() Topics: [Jetson](), [Robotics](), [Embedded Systems](), [Microcontroller](), [Jetson Orin](), [SOC](), [cpu](), [Arm](), [real-time](), [GPU](), [Linux](), [Nvidia]() Tags: [arm](), [artificial-intelligence-ai](), [camera](), [computer-vision](), [cortex-a78](), [cpu](), [deep-learning](), [development-kit](), [dfrobot](), [edge-ai](), [embedded](), [embedded-systems](), [gpu](), [hardware](), [jetson](), [jetson-orin](), [linux](), [mcu](), [networking](), [nvidia](), [os](), [processors](), [real-time](), [robotics](), [ros](), [safety](), [sensor](), [sensors](), [single-board-computer](), [soc](), [software](), [som](), [specifications](), [systems](), [ubuntu]() ### AI overview The D-Robotics RDK S100P is a robotics single-board computer featuring a 6-core Cortex-A78AE CPU, 4-core Cortex-R52+ MCU domain, 128 TOPS INT8 Nash BPU, Mali-G78AE GPU, and 24 GB of LPDDR5. Its MCU supports real-time motor and sensor control, potentially reducing the need for a separate real-time controller depending on the robot's requirements. ### Source excerpt D-Robotics RDK S100P development kit is a robotics SBC built around an S100P-based module providing an alternative to NVIDIA Jetson Orin NX 16GB with a 6-core Cortex-A78AE application cluster, a 4-core Cortex-R52+ MCU domain, a Nash BPU rated at 128 TOPS INT8, a Mali-G78AE GPU, and 24 GB of LPDDR5. The four R52+ cores can be configured for reliable real-time control: two cores run in lockstep for safety, and the other two support split-lock operation. In practice, the A78AE CPU and BPU can handle Linux and vision processing, while the MCU handles time-critical tasks such as motor and sensor I/O. This can reduce the need for a separate real-time controller, although whether it eliminates one depends on the robot and its requirements. RDK S100P specifications: SoC - D-Robotics S100P CPU - 6x Arm Cortex-A78AE @ 2.0 GHz (safety-capable AE cores) MCU - 4x Arm Cortex-R52+ @ 1.2 GHz (1x DCLS [...] The post D-Robotics RDK S100P - A 128 TOPS alternative to NVIDIA Jetson Orin NX 16GB with Cortex-A78AE/R52+ cores appeared first on CNX Software - Embedded Systems News. ## ESPHome launches a Starter Kit with four modules and an ESP32-C6 microcontroller DevFeed: [ESPHome launches a Starter Kit with four modules and an ESP32-C6 microcontroller]() Original publisher: [Read original article]() Author: Paulus Schoutsen Published: 2026-08-12T00:00:00Z Content type: release Language: en Sources: [ESPHome - Smart Home Made Simple - Blog](), [Home Assistant]() Topics: [Home Assistant](), [ESP32](), [Microcontroller](), [Hardware](), [Automation]() Tags: [announcements](), [automation](), [electronics](), [esp32](), [esp32-c6](), [esphome](), [home-assistant](), [product](), [sensor](), [smart-home](), [usb]() ### AI overview ESPHome has launched its first official product, a Starter Kit produced by Apollo Automation. It includes four modules--motion, temperature and humidity, notification, and button--built around an ESP32-C6 microcontroller and designed to work with Home Assistant. ### Source excerpt Back in April during State of the Open Home 2026, we gave you a sneak peek of ESPHome's very first official product... And after months of hard work alongside the community, the ESPHome Starter Kit is here! 🎉 ## Codename One's Cross-Platform Health API and Its Privacy Design DevFeed: [Codename One's Cross-Platform Health API and Its Privacy Design]() Original publisher: [Read original article]() Author: Shai Almog Published: 2026-08-01T00:00:00Z Content type: article Language: en Sources: [CodeName One]() Topics: [API](), [Android](), [iOS](), [Bluetooth](), [simulator](), [Testing]() Tags: [android](), [api](), [bluetooth](), [ios](), [privacy](), [sensor](), [simulator](), [testing]() ### AI overview This article examines Codename One's cross-platform health API for HealthKit, Health Connect, workouts, nutrition, Bluetooth health sensors, and deterministic simulation. It explains capability-based behavior, privacy-preserving permission handling, unit-aware samples, and cross-platform result normalization. ### Source excerpt A deep look at Codename One's HealthKit, Health Connect, workout, nutrition, Bluetooth sensor, and simulator API, including the privacy rules that shape its unusual design. ## Creating an environmental logger - Part 1 DevFeed: [Creating an environmental logger - Part 1]() Original publisher: [Read original article]() Author: John Lee Published: 2026-07-15T00:00:00Z Content type: tutorial Language: en Sources: [Blog on Developer Portal]() Topics: [ESP32](), [ESP-IDF](), [Logging](), [Terminal](), [Internet of things](), [data](), [Library]() Tags: [article](), [blog](), [esp-idf](), [esp32](), [filesystem](), [how-to](), [i2c](), [iot](), [logging](), [sensor](), [vs-code]() ### AI overview This tutorial explains how to build an environmental logger with an ESP32-C61-Devkit-C, a DHT20 temperature and humidity sensor, and ESP-IDF. Part 1 covers reading the sensor over I2C and storing measurements in a little_fs filesystem on the module's flash memory. ### Source excerpt This article shows how to create a simple environmental logger using the DHT20 sensor and store the data on a little_fs filesystem on the module's flash memory. ## Tetragon 1.7 adds fentry sensing, environment variable capture, parent-process visibility, and scoped policies DevFeed: [Tetragon 1.7 adds fentry sensing, environment variable capture, parent-process visibility, and scoped policies]() Original publisher: [Read original article]() Author: Paul Arah Published: 2026-06-09T14:01:46Z Content type: release Language: en Sources: [Isovalent - The latest articles covering eBPF-based Networking, Observability, and Security]() Topics: [Processes](), [Environment Variables](), [context]() Tags: [cilium](), [ebpf](), [environment-variables](), [hubble](), [isovalent](), [kubernetes-networking](), [load-balancer](), [mesh-networking](), [policy](), [process](), [runtime-security](), [sensor](), [tetragon](), [visibility](), [website]() ### AI overview Tetragon 1.7 introduces a new fentry sensor, environment variable capture, parent-process visibility, and granular policy scoping with hostSelector. ### Source excerpt Tetragon 1.7 introduces a new fentry sensor, environment variables capturing, parent process visibility, granular policy scoping with hostSelector and more! ## The test suite as a regression sensor DevFeed: [The test suite as a regression sensor]() Original publisher: [Read original article]() Author: Martin Fowler (martin@martinfowler.com) Published: 2026-05-27T15:01:00Z Content type: article Language: en Sources: [Martin Fowler]() Topics: [AI-assisted coding](), [coding](), [Code quality](), [React](), [TypeScript](), [Front end](), [Back end](), [mutation-testing](), [Web](), [dashboards](), [data]() Tags: [agents](), [ai](), [apis](), [backend](), [code](), [code-quality](), [coding-agents](), [data](), [frontend](), [react](), [sensor](), [skip-home-page](), [testing](), [typescript](), [web]() ### AI overview This article examines how maintainability sensors can help coding agents and developers detect declining internal code quality and support self-correction. It discusses functional correctness, architectural fitness, maintainability, codebase structure, and the use of test suites as regression sensors, including mutation testing. The examples use an internal analytics dashboard built with TypeScript, NextJS, and React, with a backend that combines data from external APIs. ### Source excerpt Birgitta Böckeler finishes her post on sensors for coding agents by examining the role of a test suite as a regression sensor, focusing on the role mutation testing can play. more... ## Run for your money: Engineering a treadmill that prints store credit DevFeed: [Run for your money: Engineering a treadmill that prints store credit]() Original publisher: [Read original article]() Author: Nikola Draca Published: 2025-11-25T13:31:13Z Content type: article Language: en Sources: [Shopify Engineering](), [Shopify Engineering - Shopify Engineering]() Topics: [Shopify](), [Extension](), [Barcode](), [real-time](), [Python](), [Socket.IO](), [Hardware]() Tags: [checkout](), [code](), [customer](), [data](), [engineering](), [events](), [extensions](), [hardware](), [python](), [real-time](), [retail](), [sensor](), [shopify](), [ui]() ### AI overview Shopify and Endorphins Running built a gamified manual treadmill for the 2025 NYC marathon weekend. A pace sensor sent Bluetooth FTMS data to a Python script, while Socket.IO and a Shopify POS UI extension connected the running experience to store-credit redemption. Participants earned credit for maintaining a selected pace and received a barcode for applying their discount at checkout. ### Source excerpt We combined FTMS sensors, Socket.IO, and POS UI extensions to turn a manual treadmill into a discount-printing machine. ## IoT for fun and Prophet: Scaling IoT and predicting the future DevFeed: [IoT for fun and Prophet: Scaling IoT and predicting the future]() Original publisher: [Read original article]() Author: Bryan Wood Published: 2025-07-22T00:00:00Z Content type: tutorial Language: en Sources: [Redpanda]() Topics: [Apache Iceberg](), [Internet of things](), [Redpanda-Connect](), [Streaming](), [Time Series](), [ESP32](), [Amazon Web Services](), [Amazon S3](), [schema-evolution](), [event driven](), [Hardware](), [Kafka]() Tags: [apache-iceberg](), [apache-iceberg-for-scalable-storage](), [aws](), [core](), [devices](), [esp32-mqtt-iot-example](), [event-driven](), [hardware](), [integrating-iceberg-and-redpanda](), [iot](), [iot-data-pipeline-architecture](), [iot-predictive-analytics](), [iot-sensor-data-forecasting](), [predictive-analysis-with-iot](), [prophet-forecasting-for-iot](), [real-time-iot-data-streaming](), [redpanda-connect](), [redpanda-connect-for-iot](), [s3](), [scaling-iot-with-prophet](), [schema-evolution](), [schema-management-in-iot](), [sensor](), [streaming](), [thought-leadership]() ### AI overview This tutorial presents a scalable IoT data pipeline for real-time streaming and forecasting. It combines Redpanda and Redpanda Connect for ingestion and messaging, Apache Iceberg for scalable time-series data storage, AWS IoT for device-to-cloud communication, and ESP32 hardware for affordable connected-device experiments and deployments. ### Source excerpt Check out this real-world example of scaling IoT for predictive analysis with Redpanda, Iceberg, and Prophet--without high costs or complexity. ## NuttX for Motor Control and Sensing: IMU Integration and Wireless Data Streaming DevFeed: [NuttX for Motor Control and Sensing: IMU Integration and Wireless Data Streaming]() Original publisher: [Read original article]() Author: John Lee Published: 2025-07-04T00:00:00Z Content type: tutorial Language: en Sources: [Blog on Developer Portal]() Topics: [ESP32-C6](), [NuttX](), [Embedded Software Dev](), [Streaming](), [Hardware](), [Espressif]() Tags: [apache](), [blog](), [embedded](), [esp32](), [esp32-c6](), [espressif](), [hardware](), [how-to](), [i2c](), [imu](), [motor](), [nuttx](), [sensor](), [streaming](), [wi-fi](), [wireless]() ### AI overview This tutorial extends a NuttX motor-control system on the ESP32-C6 with MPU6050 IMU integration for vibration measurement and wireless sensor-data streaming over Wi-Fi to a host computer for visualization and analysis. ### Source excerpt This article extends the NuttX motor control system with inertial measurement unit (IMU) sensor integration for vibration measurement and wireless data streaming capabilities using the ESP32-C6 Wi-Fi connectivity. ## Top AI agent use cases across industries | Redpanda DevFeed: [Top AI agent use cases across industries | Redpanda]() Original publisher: [Read original article]() Author: Artem Oppermann Published: 2025-06-10T00:00:00Z Content type: article Language: en Sources: [Redpanda]() Topics: [AI Agent](), [Artificial Intelligence](), [autonomous vehicles](), [real-time](), [Reinforcement learning](), [Simulation](), [data](), [Security]() Tags: [ai](), [ai-agent](), [ai-agent-applications](), [ai-agent-capabilities](), [ai-agent-technology-advancements](), [ai-agent-use-cases](), [ai-agents-in-autonomous-vehicles](), [ai-decision-making-models](), [ai-for-efficiency-in-industries](), [ai-in-cybersecurity](), [autonomous-vehicles](), [camera](), [fundamentals](), [intelligent-virtual-assistant-ai](), [natural-language-processing-ai](), [radar](), [real-time](), [real-world-ai-agent-examples](), [reinforcement-learning](), [safety](), [sensor](), [sensor-fusion-in-ai-agents](), [sensors](), [simulation]() ### AI overview This article explains what distinguishes an AI agent from ordinary software and surveys AI agent use cases across industries. It focuses on autonomous vehicles, describing how perception, decision-making, control, sensor fusion, simulation, reinforcement learning, and safety protocols support real-time operation. ### Source excerpt Learn how AI agents are being used in the real world to solve problems, boost efficiency, and make work easier across different industries. ## How to create an ESP-IDF component DevFeed: [How to create an ESP-IDF component]() Original publisher: [Read original article]() Author: John Lee Published: 2024-12-02T00:00:00Z Content type: tutorial Language: en Sources: [Blog on Developer Portal]() Topics: [ESP-IDF](), [Embedded Software Dev](), [Embedded Systems](), [Development](), [ESP32](), [Hardware]() Tags: [architecture](), [blog](), [code](), [component](), [components](), [driver](), [embedded](), [embedded-systems](), [esp-idf](), [esp-idf-component](), [esp32-c3](), [hardware](), [how-to](), [i2c](), [library](), [maintenance](), [project](), [registry](), [reuse](), [sensor]() ### AI overview This tutorial explains how to create and add project components in ESP-IDF. It covers component structure, placement in an application or separate project, and an example sensor driver for an I2C device using an ESP32-C3 development board with an integrated SHTC3 sensor. ### Source excerpt Using a monolithic architecture to develop complex applications tightly integrated with all the business logic, peripheral drivers, protocols, cloud connectivity, and so on, might sound like a nightmare. Yet, this is common in embedded systems, because it helps keep the resource overhead to the minimum. Inevitably, such approach makes collaborative development, maintenance, and reuse of code challenging to say the least. ## Build and Deploy an MQTT-Triggered Spin Application on Kubernetes DevFeed: [Build and Deploy an MQTT-Triggered Spin Application on Kubernetes]() Original publisher: [Read original article]() Author: Kate Goldenring Published: 2024-10-22T12:00:00Z Content type: tutorial Language: en Sources: [Fermyon - Experience the next wave of cloud computing.]() Topics: [App](), [MQTT](), [Internet of things](), [Kubernetes]() Tags: [app](), [build](), [deploy](), [how-to](), [iot](), [kubernetes](), [mqtt](), [sensor](), [sound]() ### AI overview A tutorial on building a Spin application triggered by an MQTT-based sound sensor and deploying it to a Kubernetes cluster with SpinKube. ### Source excerpt Learn how to build a Spin application that is triggered by an MQTT-based sound sensor and deploy that application to a Kubernetes cluster with SpinKube ## Using ESP-NOW in Arduino DevFeed: [Using ESP-NOW in Arduino]() Original publisher: [Read original article]() Author: John Lee Published: 2024-08-06T00:00:00Z Content type: tutorial Language: en Sources: [Blog on Developer Portal]() Topics: [Arduino](), [ESP32](), [Library](), [P2P](), [Protocol (disambiguation)](), [Low Latency](), [Programming](), [Encryption](), [Internet of things]() Tags: [arduino](), [arduino-ide](), [article](), [automation](), [battery](), [blog](), [c-plus-plus](), [communication](), [encryption](), [esp-now](), [esp32](), [esp32-c3](), [esp32-c6](), [esp32-s2](), [esp32-s3](), [examples](), [getting-started](), [how-to](), [iot](), [latency](), [low-power](), [microcontrollers](), [networks](), [scalability](), [sensor](), [wi-fi](), [wireless]() ### AI overview This tutorial explains how to use the ESP-NOW library included in Arduino 3.0.0 with supported ESP32 boards. It covers the protocol's connectionless peer-to-peer communication, low-latency and low-power characteristics, security features, prerequisites, and basic setup using Arduino and C++. ### Source excerpt This article presents information on how to use ESP-NOW with the Arduino core for Espressif devices. ## Automating garage doors with Shelly1, ESP8266, sensors, and HomeKit DevFeed: [Automating garage doors with Shelly1, ESP8266, sensors, and HomeKit]() Original publisher: [Read original article]() Author: Carlos Alexandro Becker Published: 2023-11-07T00:00:00Z Content type: tutorial Language: en Sources: [Carlos Becker]() Topics: [Homekit](), [ESP8266](), [Embedded Software Dev]() Tags: [esp8266](), [firmware](), [homekit](), [integration](), [sensor]() ### AI overview The article documents a HomeKit integration for two garage doors using Shelly1 relays, an ESP8266, garage-door contact sensors, and modified remotes. The second design uses sensor state to choose whether to open or close the door. ### Source excerpt This is how I automated my garage doors without using a BTN interface. ## New in PostgreSQL 14: What every developer should know DevFeed: [New in PostgreSQL 14: What every developer should know]() Original publisher: [Read original article]() Author: Gurjeet Singh Published: 2021-11-28T07:00:00Z Content type: article Language: en Sources: [Supabase Blog]() Topics: [PostgreSQL](), [Databases](), [JSON](), [data]() Tags: [database](), [developer](), [features](), [json](), [metrics](), [postgresql](), [release](), [sensor]() ### AI overview A developer-focused overview of PostgreSQL 14, covering JSON subscripting, noncontiguous data ranges, and query pipelining, along with examples of working with sensor data and application objects. ### Source excerpt A quick look at some new features and functionality in PostgreSQL 14. ## ESP32-S2 Chip Enters Mass Production DevFeed: [ESP32-S2 Chip Enters Mass Production]() Original publisher: [Read original article]() Author: John Lee Published: 2020-03-10T00:00:00Z Content type: release Language: en Sources: [Blog on Developer Portal]() Topics: [Esp32 S2](), [Microcontroller](), [Wi-Fi](), [Internet of things](), [Security](), [USB]() Tags: [blog](), [esp32-s2](), [espressif](), [iot](), [mcu](), [security](), [sensor](), [touchscreen](), [usb](), [wi-fi]() ### AI overview Espressif announces that the ESP32-S2 chip has entered mass production. The Wi-Fi-enabled MCU targets low-cost, low-power connected sensors and supports features including programmable GPIOs, USB-OTG, capacitive touch sensing, LCD interfaces, audio interfaces, and security capabilities. ### Source excerpt Why Is ESP32-S2 Significant?# We launched the ESP32-S2 chip and we are excited to announce that it is in mass production now. Personally, I think it's a big thing; it's something we have been working for, for many years: a Wi-Fi enabled MCU targeting connected low-cost low-power interactive sensors with these features: All these features add up to be a self-contained small form factor connected interactive secure computing and sensor device with a small LCD, such as a thermostat or a smart... ## ResearchStack Case Study - Jeff Namnum DevFeed: [ResearchStack Case Study - Jeff Namnum]() Original publisher: [Read original article]() Published: 2016-03-09T18:40:22Z Content type: article Language: en Sources: [Touchlab | Enterprise Mobile Innovation & Development]() Topics: [Android](), [App](), [data](), [webcam]() Tags: [android](), [case-study](), [data](), [open-source](), [sensor]() ### AI overview This case study describes touchlab's work building ResearchStack, an Android counterpart to Apple's ResearchKit, to expand digital medical research to Android users. It explains how ResearchStack supports study participation, survey data collection, and health-data analysis, and presents Mole Mapper as its first proof-of-concept app. ### Source excerpt Last fall, touchlab was approached by long-time friend and founder of Open mHealth, David Haddad, to build the Android version of Apple's ResearchKit™