Bluetooth Low Energy (BLE) Jobs

I have an ESP32 dev board on my bench and need it turned into a compact sensor hub. The entire focus is sensor integration—specifically motion & proximity plus light & sound. Some of the devices will be hard-wired to GPIO pins while others should connect wirelessly, so the firmware must handle both connection paths seamlessly. Here’s exactly what I need delivered: • Well-commented source code (Arduino-ESP32 or ESP-IDF) that polls each sensor, filters noise, and publishes readings over Serial and MQTT. • A clear wiring / pin-out diagram for the hard-wired sensors. • Configuration notes that let me pair or re-pair any wireless sensor modules. • A short README covering library installs, flash commands, and expected output. Acceptance criteri...

We are looking for an experienced Embedded Firmware Developer to program firmware for a sauna control hardware device. The PCB and hardware are already designed and working, and we now need a skilled developer to implement and optimize the firmware. This device will control sauna temperature, timers, safety features, and communicate with a mobile application (iOS & Android). Project Overview We have built a custom sauna control hardware board that will allow users to control and monitor their sauna .The firmware should handle the device logic and also enable communication between the hardware and the mobile application. The mobile app will allow users to: Turn sauna ON / OFF Adjust temperature settings Set timers Monitor current temperature Receive status updates from the dev...

I need help setting up a flow monitor that uses an ESP32 microcontroller device. This device needs to communicate with a Wi-Fi hub and send data to an app on both Android and iOS platforms. Requirements: - Communicate with a Wi-Fi hub - Send volume data per designated time period - Compatible with both Android and iOS apps Ideal skills and experience: - Experience with ESP32 and microcontrollers - Proficiency in Wi-Fi communication protocols - Mobile app development (Android and iOS) - Knowledge in data transmission and monitoring Please provide your past relevant work experience and approach to complete this task.

1. Real-time Mesh Proximity Architecture Description: Establish a proximity-based mesh positioning network between the Master device (Coordinator) and Member devices (Nodes). Technical Approach: Utilize Bluetooth Low Energy (BLE) and Wi-Fi Direct to estimate relative distance. Requirements: The Master device must continuously receive signals from Nodes. If the RSSI (Received Signal Strength Indicator) of a Node drops below a predefined threshold (corresponding to a configured physical distance), the Master must trigger an alert notification. 2. Zero-touch Check-in Authentication Description: The system automatically scans and confirms the presence of Nodes within connection range. Technical Approach: The Master broadcasts a multicast packet via local network or Bluetooth. Nodes r...

We are looking for an experienced IoT/ESP32 developer to assist with hardware connections and configuration for a Weather Monitoring System. We already have the hardware components available. We need guidance and support specifically for: • Proper sensor wiring with ESP32 • Power management guidance • Basic testing to ensure correct readings This is not a full development project — the primary focus is on hardware integration and correct connections. ⸻ Hardware Components: • ESP32 • BMP280 (Pressure + Altitude) • DHT11 (Temperature + Humidity) • MQ135 (Air Quality) • Rain Sensor ⸻ Scope of Work: • Guide on wiring setup • Assist in verifying sensor readings • Help troubleshoot if readings are incorrect • Sug...

1. Project Objective To build a high-performance mobile application capable of seamless speech-to-speech and text translation without an internet connection. 2. Technical Stack AI Models: * Translation (NMT/LLM): Quantized (4-bit/8-bit) SLMs, specifically Gemma 2 2B, Llama 3.2 (1B/3B), or Phi-3.5 Mini. Speech-to-Text (STT): Offline Whisper models (Tiny or Base variants). Text-to-Speech (TTS): Integration of system libraries (Google TTS for Android / AVFoundation for iOS). Deployment Frameworks: * Inference Engines: Google MediaPipe LLM Inference API, TensorFlow Lite, or ONNX Runtime. Hardware Acceleration: Mandatory optimization for NPU and GPU (Apple A-series, Snapdragon, and Dimensity) to ensure energy efficiency. Development Platforms: Native development (Swift for iOS, Kotlin fo...

1. Project Objective To build a high-performance mobile application capable of seamless speech-to-speech and text translation without an internet connection. 2. Technical Stack AI Models: * Translation (NMT/LLM): Quantized (4-bit/8-bit) SLMs, specifically Gemma 2 2B, Llama 3.2 (1B/3B), or Phi-3.5 Mini. Speech-to-Text (STT): Offline Whisper models (Tiny or Base variants). Text-to-Speech (TTS): Integration of system libraries (Google TTS for Android / AVFoundation for iOS). Deployment Frameworks: * Inference Engines: Google MediaPipe LLM Inference API, TensorFlow Lite, or ONNX Runtime. Hardware Acceleration: Mandatory optimization for NPU and GPU (Apple A-series, Snapdragon, and Dimensity) to ensure energy efficiency. Development Platforms: Native development (Swift for iOS, Kotlin fo...