Element14 Design challeng

https://community.element14.com/challenges-projects/design-challenges/smart-security-and-surveillance/dc/dc/81/smart_security_and_s

using the device https://os.mbed.com/platforms/MAX32630FTHR/

after a bunch of prompting, this was AI suggested as a winning entry

VolkWatch — AI-Powered Wildlife vs Human Intruder Perimeter Sentry

Project Description

VolkWatch is an AI-enabled smart perimeter sentinel designed for remote outdoor environments such as campsites, scout jamborees, conservation zones, and rural properties. Its purpose is to distinguish between natural wildlife activity and genuine human intrusions using on-device machine learning models running at the edge on the Analog Devices MAX32630FTHR platform. Traditional motion sensors often generate nuisance alarms from animals or environmental noise, reducing trust in security alerts; VolkWatch solves this by combining multi-sensor data (acoustic signatures, motion patterns, vibration features, and radio spectrum analysis) to make real-time, confidence-based classifications without relying on cloud connectivity.

Leveraging TinyML techniques and TensorFlow Lite Micro, VolkWatch extracts spectral and temporal features from ambient sound and motion in real time, feeding them into a compact neural network that classifies events as Human, Animal, or Noise/Environment. The system wakes from low-power sleep only when significant events are detected, maximizing battery life for extended remote deployment. Upon classification of a human intrusion, the node triggers local alerts (LED, buzzer) and can optionally transmit secure notifications via low-power wireless (e.g., LoRa or BLE), making it suitable even in low-connectivity environments.

This project will fully utilize features of the MAX32630FTHR kit — including its low-power Cortex-M4F MCU, audio sampling, sensor inputs, and display modules — to demonstrate an effective AI-at-the-edge security prototype. The build log will cover requirements analysis, sensor integration, embedded TinyML model training and optimization, hardware prototyping, firmware design, and real-world testing under outdoor conditions.

Getting the MAX32630FTHR

Sensors