IoT Device Design: Predictive Maintenance & Leak Detection
Publicada el 2026-07-18
Descripción de la oferta
Project Title: Low-Power Cellular IoT Predictive Maintenance & Leak Detection System Project Overview: We are seeking an experienced developer to design and prototype an integrated, low-power, battery-operated IoT device utilizing an off-the-shelf cellular prototyping architecture (e.g., Particle Boron or Blues Wireless Notecard). The device will perform twin monitoring tasks: physical leak detection via a traditional sensor, and mechanical predictive maintenance via Acoustic Anomaly Detection (AAD). The system must run on a battery budget that supports deep sleep, waking up instantly on a leak interrupt or periodically on a timer to perform a self-test and acoustic health assessment. Data must route through a cloud middleware layer via webhooks to a custom website dashboard, with critical alerts natively triggering SMS notifications. Key Hardware & Firmware Deliverables: Low-Power Firmware Development: Program the microcontroller to remain in deep sleep, waking instantly via a hardware interrupt (leak sensor) or via a scheduled monthly timer (self-test). Sensor Integration: Interface a physical leak detector and an ultra-low-power MEMS microphone (for audible or ultrasonic mechanical failure signatures) with the main board. Edge Processing (FFT/Edge AI): Implement lightweight local audio processing (e.g., Fast Fourier Transform or a TinyML model via Edge Impulse) so the device analyzes sound profiles locally and only transmits compact frequency/anomaly metrics rather than raw audio streams. Battery Monitoring: Read and transmit battery voltage and fuel gauge data during every check-in. Cloud & Web Integration Deliverables: Data Routing: Configure cloud webhooks (Particle Console or Blues Notehub) to forward compact JSON data payloads securely to our web backend endpoint. SMS Gateway Integration: Implement cloud-side routing to trigger instantaneous emergency SMS alerts via Twilio when a leak or critical acoustic anomaly is detected. Backend & Dashboard Architecture: Build a secure API endpoint to ingest incoming data, set up a relational database to track device history, establish a queued downlink mechanism to "prod" the device for on-demand tests, and build a clean frontend dashboard showing asset health status. Contractor Qualifications Skills & Knowledge Base Embedded Programming: Proficiency in C/C++ for microcontrollers, specifically with low-power state-machine architecture and deep-sleep management. Signal Processing & Edge AI: Strong grasp of digital signal processing (DSP), including implementing Fast Fourier Transforms (FFT) or developing embedded machine learning models for audio analysis using platforms like Edge Impulse. IoT Cloud Architecture: Experience configuring cloud-to-web pipelines, webhooks, API keys, JSON payload formatting, and cellular data optimization. Full-Stack Web Development: Competence in building secure RESTful API endpoints, managing relational databases (SQL) or NoSQL data stores, and crafting basic frontend tracking UIs. Third-Party APIs: Direct experience integrating SMS notification services (specifically Twilio). Education & Professional Background Preferred Education: Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, Computer Science, or a closely related technical field. Equivalent Experience: A proven track record of bringing operational IoT or industrial predictive maintenance products from prototype to low-volume production will be considered in lieu of a formal degree. Interested contractors should reply with short answers to the following technical questions: Question 1: "This project requires Edge Processing (FFT or TinyML) to analyze microphone data on the chip so we don't stream raw audio over cellular. Can you briefly describe a past project where you implemented local signal processing or edge computing on a microcontroller?" Question 2: "We are planning to use an off-the-shelf cellular module like a Particle Boron or Blues Wireless Notecard. What is your experience with either of these hardware ecosystems, or a similar ultra-low-power cellular framework?" Question 3: "How do you plan to handle the remote physical testing of the prototype since you are working remotely? Do you have access to order these development boards locally?" Finally, in your reply please list "Proj-EJM394" for consideration
Skills
Fuente original: freelancer