Project Hub /IoT & Connected Devices/Smart Home & Building Automation/Privacy Preserving Smart Home Camera System

Intermediate

ESP32

₹1,500 – ₹5,000

3 – 6 Hours

Complete Kit

Privacy Preserving Smart Home Camera System

A privacy-preserving smart home camera system built using an Adafruit MEMENTO (ESP32-S3) for on-device semantic vision processing and an ESP8266 for LED indicators, communicating locally via UDP.

Originally published on CircuitDigest

View original tutorial

Parts You'll Need

This project is sourced from another site, not written by us — this list is our best match of their components against what we stock, not a verified bill of materials. Always check the original blog (linked above) for the actual parts list before buying.

10pcs 5mm RED Diffused Light Emitting Diodes - LEDs Set Rs. 39.00
ESP32 CAM WiFi Module Bluetooth with OV2640 Camera Rs. 810.00
Jumper Wire 10 Pin Male To Male 20cm Rs. 45.00
NodeMCU ESP8266 WIFI development board based on CP2102 Rs. 660.00
MB102 Adjustable Breadboard Power Supply Module (3.3V & 5V) for Arduino & Raspberry Pi Rs. 139.00
10pcs - 220 ohm 1/4 W Resistor Set Rs. 39.00
400 Points Mini Solderless Prototype PCB Breadboard High Quality Rs. 89.00
Jumper Wire 10 Pin Male To Female 20cm Rs. 45.00

Selected: Rs. 0.00

This list includes a generic resistor set as a placeholder — it is not matched to the exact value or part number this circuit needs. The correct one is specified on the original source page linked above; check it before buying.

Browse all components

How It Works

The Privacy Preserving Smart Home Camera System operates as a distributed edge-computing network designed to process visual data locally without streaming sensitive raw video to external cloud servers. At the core of the system is the Adafruit MEMENTO ESP32-S3 main board, which captures local imagery and runs on-device semantic vision processing. Instead of transmitting video feeds externally, the ESP32-S3 analyzes the scene locally to extract abstract parameters, such as room occupancy or motion states. Once a specific visual condition or event is identified, the ESP32-S3 transmits lightweight UDP network packets over a local wireless network. These UDP packets are received by the secondary ESP8266 NodeMCU microcontroller. Upon receiving a specific UDP payload, the ESP8266 drives a circuit built on a breadboard comprising four individual LEDs connected in series with four 220-ohm current-limiting resistors. These resistors are crucial for safely dropping the voltage from the digital output pins, preventing excess current from damaging the indicator LEDs. By illuminating or flashing the LEDs based on real-time UDP commands, the system provides immediate visual status feedback for activities like elderly care monitoring or occupancy detection, maintaining total data privacy by keeping all video analysis strictly on the local hardware.

Why Build This

Develop practical competence in edge-computing architectures by implementing local semantic vision processing on an ESP32-S3 without relying on external cloud infrastructure.

Master local device-to-device communication protocols by configuring UDP packet transmission between distinct microcontrollers (ESP32 and ESP8266).

Design privacy-first IoT solutions applicable to real-world engineering scenarios such as secure indoor activity monitoring and energy-efficient HVAC room occupancy detection.

Real-World Application

Elderly care monitoring, energy-efficient smart lighting, room occupancy detection for HVAC control, and secure indoor activity monitoring without compromising personal privacy.

Skills You'll Learn

Edge AI deployment

local UDP network communication

microcontroller-to-microcontroller messaging

digital GPIO control

current-limiting resistor calculations

breadboard circuit prototyping

Safety Precautions

Ensure electrical connections are properly insulated, use non-conductive surfaces to mount boards to avoid electrical shorts, and maintain proper grounding for all LED indicators.

Technology Tags

EDGE COMPUTING

COMPUTER VISION

UDP NETWORKING

PYTHON

CIRCUITPYTHON

IOT

PRIVACY-PRESERVING AI

WIRELESS COMMUNICATION

Frequently Asked Questions

Why use two different microcontrollers instead of just one?

The Adafruit MEMENTO ESP32-S3 handles the heavy computational load of camera control and on-device vision processing, while the ESP8266 NodeMCU is dedicated to receiving UDP packets and driving the LED indicator circuit, distributing the workload across the network.

Are the 220-ohm resistors strictly necessary for the LEDs?

Yes. The 220-ohm resistors limit the forward current flowing through the four LEDs, protecting both the indicator components and the digital output pins of the ESP8266 from overcurrent damage.

Does this system require an active internet connection to function?

No. The system communicates entirely over a local wireless network using UDP packets, meaning it can operate on a closed local area network without external internet access, ensuring enhanced data privacy.

Gallery

This page is part of Kitkraft's Project Hub — a curated collection of electronics & robotics projects gathered from the maker community to help students and hobbyists discover and learn to build. Kitkraft does not claim authorship of the original project, and makes no representation as to the accuracy, completeness or safety of third-party source material. The summary and "How It Works" explanation above are AI-generated, rewritten with reference to the original tutorial — not a reproduction of it. Full credit and a direct link to the original source are provided above. If you're the original creator and have a concern about how your work is represented here, please contact us and we'll address it promptly.

Kitkraft Project Hub — curated from the maker community, credited at the source.

PRJ-01351