ESP32-CAM IoT Control System
Budget: $250 – $750 USD
I have an ESP32-CAM board and want a complete, working IoT solution built around it. The core goals are real-time video streaming, advanced face recognition, and multi-channel light control, all managed from an Android mobile app.
Key requirements
• Configure the ESP32-CAM to deliver a stable, low-latency video stream.
• Integrate advanced face recognition on-device or through an efficient edge/cloud workflow that meets ESP32 performance limits.
• Drive several relay modules to switch household lights on and off.
• Expand the number of controllable outputs with 74HC595 shift registers (or a comparable serial-to-parallel IC) so the system scales beyond the ESP32’s native GPIO count.
• Build an intuitive Android app that discovers the ESP32 on the local network, shows the live video feed, displays face-recognition feedback, and lets me toggle each light channel individually or in groups.
Additional notes
– Code should be well-structured, commented, and delivered in a Git repository.
– The Android client may be native (Java/Kotlin) or built with a cross-platform toolkit, provided performance stays smooth.
– I’ll need simple instructions for flashing firmware, wiring the relays and shift registers, and compiling/running the mobile app.
– All libraries and frameworks used must be open-source or otherwise free for commercial use.
Once everything works end-to-end, I’ll test the system on my hardware setup. I’m happy to provide prompt feedback during development so we can iterate quickly.
Key requirements
• Configure the ESP32-CAM to deliver a stable, low-latency video stream.
• Integrate advanced face recognition on-device or through an efficient edge/cloud workflow that meets ESP32 performance limits.
• Drive several relay modules to switch household lights on and off.
• Expand the number of controllable outputs with 74HC595 shift registers (or a comparable serial-to-parallel IC) so the system scales beyond the ESP32’s native GPIO count.
• Build an intuitive Android app that discovers the ESP32 on the local network, shows the live video feed, displays face-recognition feedback, and lets me toggle each light channel individually or in groups.
Additional notes
– Code should be well-structured, commented, and delivered in a Git repository.
– The Android client may be native (Java/Kotlin) or built with a cross-platform toolkit, provided performance stays smooth.
– I’ll need simple instructions for flashing firmware, wiring the relays and shift registers, and compiling/running the mobile app.
– All libraries and frameworks used must be open-source or otherwise free for commercial use.
Once everything works end-to-end, I’ll test the system on my hardware setup. I’m happy to provide prompt feedback during development so we can iterate quickly.