Nabu Casa has just launched the Home Assistant Voice Preview Edition, a little ESP32 device with an XMOS XU316 audio processor, a dual-microphone array, an internal speaker, and a 3.5mm audio jack, that adds offline smart speaker functions to your Home Assistant server through WiFi. If your Home Assistant server is powerful enough, voice processing will be done directly on your local hardware using Home Assistant Voice software, but with lower-end hardware like a Raspberry Pi 4, audio processing can be done via a privacy-focused cloud instead. The solution also supports expansion thanks to a Grove connector on the bottom of the device. Voice Preview Edition specifications: SoC – Espressif ESP32-S3 dual-core Xtensa LX7 @ up to 240 MHz with vector extension for ML acceleration, 2.4 GHz WiFi & Bluetooth 5.0 LE connectivity Memory- 8 MB octal PSRAM Storage – 16 MB flash Audio DSP/Processor – XMOS XU316 with 16 [...]
LG Electronics (LG) has fully opened its ThingQ API for its Smart Home platform to enable developers to integrate their solutions with compatible LG appliances. The release covers both the API for individual users and corporate users. The ThinQ API for individual users supports the control and monitoring of AI appliances registered in the LG ThinQ app. It allows users to create customized Smart Home applications, for example, the popular Home Assistant home automation framework can already connect and control 26 types of LG AI appliances including refrigerators, water heaters, and washing machines. I can see the community has been working on LG ThinQ integration well before the release of the full release of the API, but maybe LG saw this and completly released the API to ease the work of developers. There are four main ThingQ APIs for individuals: Device API – Used to request ThinQ device information and [...]
The Hornet Nest Alarm Panel is a customizable, ESP32-based alarm control system designed and produced by US-based Technology Automation Consulting for home security automation. The device is powered by the wESP32 Ethernet board with PoE support and is compatible with Home Assistant through the ESPHome firmware. It features up to forty-two optoisolated zones, six MOSFET-controlled outputs, and six additional trigger outputs for 3.3V devices. It integrates a piezo buzzer and supports add-ons like a Wiegand keypad and water leak sensors. The Hornet Nest Alarm ESP32-based home security platform “aims to bridge the gap between traditional wired security systems and the flexibility of modern smart home automation.” Christopher Greenless of Technology Automation Consulting says the project was born from his need for a robust and smart security system to integrate with his Home Assistant setup. Proprietary solutions were inadequate and limited while DIY options were inefficient and often unreliable. He created [...]
CrowdSupply recently featured the Hornet Nest Alarm Panel, a PoE-enabled security panel that integrates traditional wired alarm systems with modern smart home platforms like Home Assistant. Its open-source design provides flexibility and customization for enhancing home security systems. The panel allows for integration with smart home ecosystems using ESPHome, it supports straightforward configuration, enabling control […]
The Pico W5 is a Raspberry Pi RP2350 development board providing an alternative to the official Raspberry Pi Pico 2 W with dual-band (2.4GHz/5GHz) WiFi 4 and Bluetooth 5.0 connectivity through a B&T BW16 wireless module. Besides dual-band WiFi, there are a few other small changes compared to the Raspberry Pi Pico 2 W, including a USB Type-C connector, a larger 8MB flash, and a Reset button. As far as I know, it’s the first RP2350 board with 5GHz WiFi, as other RP2350 boards with WiFi, such as the Challenger+ RP2350 WiFi6/BLE5 and Pimoroni Pico Plus 2 W, only support 2.4GHz WiFi. Pico W5 specifications: SoC – Raspberry Pi RP2350 CPU Dual-core Arm Cortex-M33 @ 150 MHz with Arm Trustzone, Secure boot and Dual-core RISC-V Hazard3 @ 150 MHz Only two cores can be used at any given time Memory – 520 KB on-chip SRAM Security 8KB of anti-fuse OTP [...]
Home Assistant has announced a significant upgrade to its Yellow platform with Compute Module 5 (CM5) support in HAOS 14. This expansion brings enhanced capabilities while maintaining strong support for existing CM4 users.
Home Assistant Yellow now supports CM5 (Compute Module 5)
Support will be available in the HAOS 14 release
CM5 Advantages:
Higher performance, up to 3x faster for ESPHome compilation
Better local speech-to-text processing
Suitable for power users’ needs
HAOS 14 Additional Updates:
Added support for Hailo-8 AI accelerator
AI capabilities for Pi 5
This update reinforces Home Assistant’s commitment to providing users with scalable, future-proof smart home solutions. While CM5 offers significant performance benefits for power users, CM4 remains a viable option for standard installations, demonstrating Home Assistant’s balanced approach to hardware evolution. Apart from that, CM4 production will continue and Raspberry Pi commits to support CM4 until 2034.
How to Install HAOS on CM5
Note: It’s necessary to use the latest version of rpiboot when installing Home Assistant OS for CM5. Download the latest Version.
Seeed Studio has recently launched a 2-channel Wi-Fi AC relay built around the XIAO ESP32C3 WiFI and Bluetooth module. The device is a simple WiFi relay module that can control two independent 100-240V AC appliances and is designed to be compatible with both Home Assistant with ESPHome firmware flashed by default. The device also features a built-in BL0942 power meter with a maximum load capacity of 2400W at 240V for real-time and historical energy consumption monitoring. These features make this device suitable for applications such as energy tracking and remote control of appliances. Seeed Studio 2-channel Wi-Fi AC relay specifications: MCU – XIAO ESP32-C3 with ESP32-C3 WiFi 4 and Bluetooth 5.x RISC-V microcontroller, USB-C port (unused here) Wireless connectivity – 2.4GHz Wi-Fi Relay channels – 2 independent channels Power Input terminals – Neutral (N), Live (L) Input voltage – 100-240V AC, 50/60Hz Output terminals Channel 1: N1 (Neutral), L1 (Live) [...]
Our Seeed Studio XIAO ecosystem has been growing steadily with tap-on accessories like Grove Expansion Boards, Sensors, Connectivity Modules, and Actuators to complement our thumb-sized dev boards. But one thing kept coming up in our XIAO Open Roadmap – you wanted more relays! Well, we heard you, and here’s our answer: the new Seeed Studio 2-Channel AC Wi-Fi Relay.
Powered by our thumb-sized XIAO ESP32C3, this Home Assistant-native relay device lets you control two independent 100-240V AC loads – perfect for lights, appliances, and motorized facilities. We’ve pre-flashed it with ESPHome firmware and built in a power meter, so you can track both real-time and historical power consumption right from your Home Assistant dashboard.
All the above-mentioned features make it particularly suited for applications that need both remote control and power monitoring of household electrical devices through a smart home automation system.
Want to know what’s under the hood? We’ve packed in two 10A/250VAC high-power latching relays (HF3F-L), giving you control over two loads on a 50-60 Hz AC carrier signal. Here’s a sneak peek at the internals – and don’t worry, we’ll be open-sourcing all schematics on our Wiki soon!
Oh, and one more thing! The relay comes in a white 3D-printed enclosure (which you can download and customize from Thingiverse for free). And for all you makers and developers who want to DIY with your existing XIAO boards – stay tuned! We’re working on a universal Relay Add-on that’ll be compatible with all XIAO dev boards.
Notes at the end.
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
We have received the latest tiny indoor security camera from SONOFF: the second generation of the CAM Slim series known as the CAM Slim Gen2 (or CAM S2 for shorts). Some of you might remember the first-generation CAM Slim model reviewed by Jean-Luc about two years ago. The Gen2 version keeps the same 1080p resolution but comes with several upgraded features, including AI algorithms to distinguish living beings, customizable detection zones, customizable privacy zones, sleep mode, enhanced low-light image quality, and flexible storage management. Although it’s packed with several enhancements, its price is lower than the Gen1. Let’s delve into the details! SONOFF CAM Slim Gen2 unboxing Inside the box, you’ll find a compact manual, a USB-C cable, a mounting kit, and a sticker template acting as a drilling guide. The camera is smaller than your palm and comes mounted on a versatile, rotatable base, making installation in various positions [...]
The YULC (Yes, a USB-C LED Controller) board is a compact, ESP32-S3-powered LED controller with USB-C and DC jack power inputs. It is a fully featured board that can easily replace a rat’s nest of wires and save space and time. This ESP32 LED controller features a built-in buck regulator that converts input power from the USB-C port or barrel jack to the voltage needed for the LED strips. The YULC provides two separate LED channels with a level shifter each to ensure clean and powerful data output, removing the need for a sacrificial pixel or external level shifter. Each channel also has a power MOSFET that can turn off the channels individually and dim simple LED strips via PWM. AAElectronics, the maker, has previously released an IR remote—the Home Assistant-compatible ESP 360 Remote—which we covered at the time. Similar products include the SMLIGHT A1-SLWF-03, DFRobot’s EDGE102-DMX512, and the PixelBlaze [...]
We have received another Zigbee device from SONOFF for review, namely the ZBMINIR2 which we’ll review with both eWelink adn Home Assistant. Many people may be familiar with the first-generation mini Zigbee Switch that SONOFF released in 2020, known as the ZBMINI. ZBMINI was one of the early Zigbee Switch models, which also acted as a Zigbee Router. The ZBMINIR2 is SONOFF’s second-generation mini Zigbee Switch including both software and hardware upgrades compared to its predecessor. Improvements include a smaller size, better signal quality, an increase in the number of supported devices (2x), wider coverage (5x), and additional features. Let’s dive into the details. Unboxing ZBMINIR2 Zigbee switch Inside the box, you’ll find a small user manual and the ZBMINIR2 device as usual. It is notably smaller than the predecessor model, which makes installation much easier in many cases. For example, it can now fit into the wall box behind [...]
Last year, we reviewed the MR60FDA1 60GHz mmWave fall detection sensor kit, which utilizes the XIAO ESP32C3 module as its core. This module, featuring both Wi-Fi and Bluetooth connectivity, opens up various IoT applications. Now, Seeed Studio has introduced advanced mmWave sensor modules specifically designed for enhanced fall detection and heartbeat monitoring. The MR60FDA2 is optimized for fall detection, while the MR60BHA2 is designed for heartbeat monitoring. Powered by an ESP32-C6 WiFi 6 and RIS-Bluetotoh LE microcontroller, these modules offer reliable detection for real-time fall monitoring and accurate heartbeat tracking. They also feature customizable RGB LEDs and ambient light sensors, providing additional flexibility. With expansion options via Grove GPIO ports, these versatile modules are well-suited for applications like smart home integration and healthcare monitoring. Previously, we covered the RoomSense IQ and the DesignCore RS-6843AOPU with mmWave technology. The RoomSense IQ is an ESP32-S3-based modular room monitor with mmWave radar presence [...]
Explore the best smart audio devices and microphones designed for seamless integration with Home Assistant, and partial compatibility with Amazon Alexa and Google Assistant. Whether you’re building a voice-activated smart home or a DIY audio project, these products offer high-performance sound capture and voice control.
Why You Need a Smart Speaker for Home Assistant
In a smart home setup, audio devices such as microphones and speakers play a critical role in enhancing voice control and automation. These products integrate seamlessly with Home Assistant, while some may also be compatible with Amazon Alexa or Google Assistant through additional setup. Here, we’ll explore the top ReSpeaker and Grove products that enable robust voice interaction and sound management for DIY smart home systems.
The ReSpeaker 2-Mics Pi HAT is designed for Raspberry Pi projects and features two analog microphones with high-definition voice capture capabilities. It is equipped with Voice Activity Detection and Direction of Arrival algorithms, making it perfect for local voice recognition tasks with Home Assistant and other DIY voice interaction applications.
Key Features:
Dual analog microphones and WM8960 Audio Codec for high-quality sound
Voice Activity Detection, Direction of Arrival, and Keyword Spotting capabilities
RGB LED and programmable button for customized control
This high-performance speaker is ideal for audio output in various smart home projects. It integrates easily with devices like the ReSpeaker Lite to enhance audio quality for voice commands, notifications, or media playback in Home Assistant setups.
Key Features:
Compact, enclosed design for enhanced sound quality
Suitable for smart home audio systems, robot voice output, and DIY audio projects
The ReSpeaker USB Mic Array is perfect for far-field voice recognition in larger spaces. It includes four microphones and advanced speech algorithms such as Beamforming, Noise Suppression, and Acoustic Echo Cancellation, making it ideal for voice-controlled smart home environments.
An upgrade to the original ReSpeaker Mic Array, the ReSpeaker Mic Array v2.0 is equipped with XMOS’s XVF-3000 chip and supports far-field voice capture. This version improves voice recognition accuracy, making it a robust solution for adding a voice interface to your existing or future smart home products.
Key Features:
Far-field voice recognition with four microphones
USB Audio Class 1.0 compatibility
Includes advanced algorithms like Voice Activity Detection, Direction of Arrival, and Noise Suppression
Powered by the XMOS XU316 AI Sound chip, this development board excels in audio processing and speech recognition. With its dual microphone array and support for external power supplies, it is a perfect solution for DIY smart home audio systems or voice-controlled projects.
Key Features:
Dual microphone array for far-field voice capture
Onboard AI algorithms for noise suppression and echo cancellation
Supports I2S and USB connections
Compatible with XIAO ESP32S3, Adafruit QT Py, Raspberry Pi, and PC
The Grove – Speaker module is perfect for DIY projects, providing sound amplification and voice output. Its on-board potentiometer allows for loudness control, and it is compatible with Arduino platforms for building custom sound systems or music boxes.
Key Features:
Simple module for voice output and sound generation
Platform Compatibility: Ensure the product supports the platform you’re using, whether it’s Home Assistant, Amazon Alexa, or Google Assistant. Most of these devices are compatible with ESPHome for Home Assistant integration.
Customizability: Products like the ReSpeaker Lite offer flexibility for developers, with open-source compatibility and support for multiple programming platforms.
Use Case Ideas for Home Assistant Speakers
Home Automation with Voice Control: Integrate the ReSpeaker Lite with XIAO ESP32S3 with Home Assistant to control smart devices like lights, thermostats, or security systems via voice commands.
Audio Alerts and Notifications: Use the Mono Enclosed Speaker or Grove – Speaker to generate audio alerts for events like door openings or motion detection in your smart home.
Far-Field Voice Recognition: With the ReSpeaker USB Mic Array, capture voice commands from across the room, ideal for large, open living spaces.
Conclusion
These ReSpeaker and Grove products offer robust solutions for building voice-activated smart homes or custom audio systems. While they seamlessly integrate with Home Assistant, some products may also work with Amazon Alexa or Google Assistant, though additional setup or configurations might be required. These devices provide the flexibility and performance needed to bring your DIY smart home projects to life.
Explore our range of Home Assistant-compatible speakers and take your home automation to the next level!
Al aprovechar los LLMs, Watcher puede capturar los eventos precisos que especificaste, lo
que significa ir más allá de las simples detecciones de objetivos, ya que analiza
completamente comportamientos y estados. Como “perro + jugando con la pelota, 0
personas + en la habitación”, o “La persona + con uniforme de DHL ha llegado”, etc.
¡Watcher realmente entiende la escena bajo su vigilancia!
Llamar constantemente a los LLMs como ChatGPT genera un costo elevado. Por
lo tanto, utilizamos una arquitectura de IA en el dispositivo + LLMs. El modelo de IA en el
Watcher detecta el objetivo, que luego es analizado por LLM para generar ideas precisas y
accionables.
Con la tarea “dime si el perro está rompiendo papel”, cuando el modelo del dispositivo
detecta perros, esta escena clave se envía al LLM para un análisis más profundo: ¿está
rompiendo papel? Los LLM no se activarán por personas, gatos, ardillas u otros. Esto
reduce enormemente el costo de los LLM.
Responde por voz
Después de detectar el evento especificado, Watcher puede interactuar con los objetivos a
través de la voz. Por ejemplo, puedes configurarlo de la siguiente manera:
Evento especificado: alguien toma el teclado rosa;
Dos reacciones especificadas:
1. una respuesta por voz que diga: ‘¡Buena elección! Esta es nuestra versión más
reciente, inspirada en la máquina de escribir Pink Royal’;
2. la otra reacción es un mensaje de texto a los vendedores: ‘¡Alguien está interesado
en el teclado más reciente! Por favor, vayan al estante lo antes posible’.
Colocar Watcher en diferentes escenarios permite respuestas versátiles. Al ver un perro
rompiendo pañuelos, dile “¡Para, Cooper!”, o si ve a una persona fumando en áreas donde
no está permitido, dile “¡No fumar!”
¿Cómo mejorar tus sistemas? Solo necesitas un complemento
sencillo.
Una vez detectado el evento objetivo, puede activar diferentes acciones, por ejemplo, enviar
mensajes push en la aplicación SenseCraft o hacer que las luces LED de Watcher
parpadeen. Por supuesto, entendemos que quieres ir más allá de las funcionalidades en la
app o el dispositivo. ¡No hay problema! ¡Hay infinitas posibilidades para explorar!
Añade Watcher a Home Assistant.
Conectado a plataformas IoT como Home Assistant, tu Watcheractúa como un
sensor de comportamiento, activando acciones personalizadas en diversos contextos. Por
ejemplo, cuando detecta personas, Watcher analiza la situación y automáticamente
desencadena acciones: luces encendidas para leer y luces apagadas para dormir.
Más que un sensor de visión, Watcher se puede ampliar con otros sensores
para habilitar la detección multimodal. En la parte trasera de Watcher, el I2C está
reservado para acomodar más de 100 sensores Grove. Esta flexibilidad permite queWatcher integre una amplia gama de fuentes de datos para un análisis exhaustivo y
acciones apropiadas. Podrás construir aplicaciones como detectar la temperatura de la
habitación y ajustar el aire acondicionado en consecuencia: cambiarlo a 22°C cuando llevas
traje, o a 26°C cuando estás en shorts.
Añade Watcher a tu flujo de Node-RED
A solo 3 bloques de distancia, puedes transmitir los resultados detectados por tu Watcher a
cualquier lugar en internet a través de Node-RED, ¡tan fácil como hacer clic!
Añade Watcher a tu Arduino | ESP32 y otros sistemas de
hardware.
¿Quieres añadir un agente de IA a los MCU y SBC populares como
Arduino/ESP32/Raspberry Pi? Simplemente conéctalo a Watcher a través de UART, HTTP o
USB, y podrás explorar la nueva frontera de la inteligencia.
Dato curioso: Aquí en Seeed, Watcher tiene el apodo de “Nobody,” simbolizando
un robot sin cuerpo. Esto transmite un mensaje poderoso: ¡Dale a Watcher un cuerpo!
¡Watcher puede ser una cabeza genial para tu robot!
Para los fans de XIAO, ¡tenemos un paquete especial! Apoya a SenseCAP
Watcher y podrás añadir un XIAO ESP32C6 por solo $1.
XIAO ESP32C6 es un MCU compacto, nativo de Matter, para hogares inteligentes. Basado
en ESP32-C6 de Espressif, soporta diversas conectividades inalámbricas: Wi-Fi 6 a 2.4
GHz, BLE 5.0, Zigbee y Thread.
Por ejemplo, puedes hacer un sensor de emociones añadiendo Watcher a XIAO.
Al detectar tu mal humor, florece para animarte.
Dale emociones únicas a tu Watcher
SenseCAP Watcher se adapta a tus comandos con “modos” únicos. Primero ESCUCHA tus
instrucciones, luego cambia al modo de VIGILANCIA para proteger el espacio designado,
etc. ¡Pero la diversión no termina aquí! Puedes subir tus propios diseños de emociones
para darle a tu Watcher una personalidad única. ¡Prepara un archivo PNG y súbelo a
Watcher en segundos! ¡Es tu decisión!
Los emojis predeterminados de Watcher están inspirados en C-3PO, en homenaje a uno de
nuestros mayores ayudantes.
Puedes subir los tuyos fácilmente en formato .PNG
Incluso puedes diseñar una interfaz de usuario (UI) única para tu SenseCAP
Watcher. Nuestra interfaz actual está impulsada por Squareline.
Open Source y despliegue On-Premise.
Como un dispositivo de IA, es fundamental respetar la privacidad. Y adoptamos e
implementamos dos estrategias clave en este ingenioso dispositivo.
1. SenseCAP Watcher es de código abierto, lo que te brinda acceso completo para
entender a fondo cómo funciona.
2. Soporta despliegue on-premise. La columna vertebral de SenseCAP Watcher es la
suite de software SenseCraft, que se utiliza para configurar Watcher, interpretar tus
comandos y acceder a los LLMs. Por lo tanto, todo está almacenado y ejecutándose
de manera privada, garantizando que tus modelos y datos no se envíen a ningún
LLM o nube pública. SenseCraft puede ejecutarse en Windows/MacOS/Linux. Dado
que SenseCraft contiene LLMs, ciertos criterios de rendimiento son necesarios para
la computadora, como se detalla a continuación.
Puedes desplegar SenseCraft en tus computadoras de repuesto. Sin embargo, si
buscas aplicaciones que requieran confiabilidad a nivel comercial y bajo consumo de
energía, la combinación de SenseCAP Watcher + NVIDIA® Jetson AGX Orin es perfecta
para ti.
En comparación con las tarjetas gráficas de consumo (como la RTX 4090) para
tareas de IA, NVIDIA® Jetson AGX Orin destaca con ventajas clave:
1. Confiabilidad a nivel industrial: Diseñada para aplicaciones industriales y
comerciales, la serie Jetson AGX cuenta con un MTBF (tiempo medio entre fallas)
más largo. Diseñada para operar las 24 horas del día, ofrece una confiabilidad
superior para aplicaciones de funcionamiento continuo, en comparación con las
tarjetas gráficas de consumo.
2. Compacta y de bajo consumo: Con aplicaciones de computación embebida y en el
borde en mente, la serie Jetson AGX está diseñada en un formato más pequeño y
consume más de 3 veces menos energía que las tarjetas gráficas de consumo. Es
adecuada para espacios reducidos, genera menos calor y ayuda a reducir los costos
operativos. Esto es crucial para los sistemas embebidos.
¿Suscripción? ¡Tú decides!
Los Servicios de IA de SenseCraft están diseñados para tus necesidades.
Empieza con Basic, completamente GRATIS para baja frecuencia: 15 minutos/solicitud para
análisis de imágenes, 200 chats/mes con LLMs.
¿Necesitas más? Solo $6.90 para la versión Pro, paga solo por lo que consumes, ¡SIN
compromiso de tarifas recurrentes! Además, ¡cada dispositivo NUEVO incluye un
paquete Pro GRATIS de $6.90! Recarga según sea necesario.
¿Quieres evitar tarifas por completo? Elige On-Premise. Simplemente despliega y usa sin
costos adicionales.
Dos modelos
Soporte para varios métodos de montaje.
Se puede colocar sobre un escritorio o montarlo en paredes como una expansión
inteligente. O también se puede transformar en la cabeza de un robot.
Otros lo usaron como
Personalización – El camino más rápido para construir hardware
con IA.
El próximo dispositivo debería estar impulsado por IA. ¡El hardware con IA incorporada
conectada a LLMs es la tendencia!
Con SenseCAP Watcher, hemos desarrollado un marco revolucionario que lleva potentes
LLMs al borde del mundo físico. Este marco acelera el prototipado de hardware con IA. Con
nuestros servicios de personalización, ¡puedes dar vida a tu hardware de IA más rápido que
nunca!
¡Es hora de aumentar la inteligencia de tu espacio! Estamos en
Hemos realizado pruebas exhaustivas con SenseCAP Watcher, y estamos completamente
comprometidos a entregarlo a tiempo a nuestros patrocinadores, con todo funcionando sinproblemas. No obstante, como sucede con cualquier nuevo producto, existen riesgos
potenciales asociados al lanzamiento.
Sin embargo, como una empresa consolidada con un historial probado de éxito en el
desarrollo de cientos de productos, sabemos cómo superar estos desafíos. Ten la seguridad
de que, si surgen problemas de producción, seremos completamente transparentes con
nuestros patrocinadores y los mantendremos informados durante todo el proceso.
Uso de la IA
Tengo pensado usar contenido generado por IA en mi proyecto.
¿Qué partes de tu proyecto utilizarán contenido generado por IA? Responde con la
mayor precisión posible.
Usaremos contenido generado por IA de MidJourney para crear imágenes que destaquen
las características de nuestro producto y muestran cómo puede ser usado en escenarios
reales. Además, utilizaré ChatGPT para la corrección de estilo de nuestra campaña.
¿Tienes el consentimiento de los propietarios de los trabajos que se usaron (o se
usarán) para producir la parte de tu proyecto generada por IA? Por favor, explica.
Para las imágenes que necesitamos, primero buscaremos en bibliotecas existentes en
Google. Si encontramos imágenes que puedan ser usadas directamente, verificaremos sus
licencias para determinar los pasos apropiados a seguir. Si las imágenes no pueden ser
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
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.
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