Project Roadmap
Relevant source files
The following files were used as context for generating this wiki page:Introduction
The HomeSecurity project currently provides a robust, IoT-based anti-intrusion system using an ESP32, multiple sensors, and Firebase for real-time notifications. It successfully implements a multi-layered detection strategy with a two-stage alert mechanism to minimize false positives. The system architecture is distributed across Edge, Cloud, and Client tiers, delivering core security features effectively.
This document outlines the planned future development for the HomeSecurity project. The roadmap focuses on enhancing the system's intelligence, security, scalability, and power efficiency. These enhancements aim to evolve the project from a functional prototype into a more comprehensive and resilient home security solution, addressing current limitations and expanding its capabilities.
Sources: HomeSecurity/README.md:25-33, 500-501
Planned Enhancements
The following table summarizes the key features planned for future releases, including their description and estimated implementation complexity.
| Feature | Description | Complexity |
|---|---|---|
| Event Logging | Store alerts in Cloud Firestore for historical analysis. | Medium |
| TinyML Integration | On-device ML for person/pet classification (using ESP32-CAM). | High |
| VPN/WebRTC | Secure video streaming without requiring port forwarding. | High |
| Battery Backup | Li-Po integration with deep sleep optimization for power efficiency. | Medium |
| Multi-Node System | ESP-NOW mesh network for whole-home coverage with multiple sensor nodes. | High |
| Voice Assistant | Integration with Google Home/Alexa for voice commands and status updates. | Medium |
Sources: HomeSecurity/README.md:502-510
Event Logging to Firestore
Currently, the system sends transient push notifications via a Firebase Cloud Function. The roadmap includes integrating Cloud Firestore to create a persistent log of all security events. This will allow users to review historical alert data within the mobile application.
This diagram illustrates the proposed change to the cloud architecture to include Firestore for event persistence.
This enhancement will modify the existing notification flow, where the cloud function, upon receiving a request from the ESP32, will not only trigger a push notification but also write an event entry to a Firestore database.
Sources: HomeSecurity/README.md:503, HomeSecurity/src/firebase_notifier.cpp:15-25
TinyML Integration for Smart Detection
To further reduce false alarms and add contextual awareness, the plan is to integrate a TinyML model on an ESP32-CAM. This will enable on-device machine learning to classify motion events, distinguishing between people, pets, or other movements. This moves intelligence to the edge, reducing reliance on cloud processing for classification.
The following flowchart shows the modified detection logic with TinyML.
This feature represents a significant evolution of the core detection logic currently found in motion_logic.cpp.
Sources: HomeSecurity/README.md:504, HomeSecurity/src/motion_logic.cpp:46-63
Secure Video Streaming
The current implementation relies on RTSP for video streaming, which may require insecure port forwarding. A future goal is to implement a more secure streaming solution using either a VPN or WebRTC. This would create a secure, encrypted tunnel between the IP camera and the client application, enhancing user privacy and system security. This also addresses the current use of an insecure WiFiClientSecure connection for notifications, indicating a broader need for enhanced security.
Sources: HomeSecurity/README.md:505, HomeSecurity/src/firebase_notifier.cpp:8
Multi-Node Mesh Network
To provide coverage for larger homes, the roadmap includes expanding the system into a multi-node mesh network using the ESP-NOW protocol. This would allow multiple, low-power sensor nodes to communicate with a central gateway ESP32, which then handles the cloud communication.
This diagram shows the proposed multi-node architecture.
This architecture would require significant changes to the firmware, moving from a single-device model to a gateway-node topology.
Sources: HomeSecurity/README.md:507
Battery Backup and Power Optimization
The system is currently designed for a constant power supply. A key enhancement is to add support for a Li-Po battery backup and implement power-saving strategies, such as deep sleep modes. This would make the system more resilient to power outages and allow for the deployment of battery-powered sensor nodes in the future multi-node architecture. The current FreeRTOS task structure would need to be re-evaluated to support deep sleep cycles.
Sources: HomeSecurity/README.md:506, HomeSecurity/src/main.cpp:8-14