- 1.Program Overview
- 2.Track Overview
- 3.Track 1 — Core Security Platform
- 4.Track 2 — Modular Architecture & Plugin System
- 5.Track 3 — Network Services Layer
- 6.Track 4 — Edge AI & On-Device Inference
- 7.Track 5 — IoT & Environmental Sensing
- 8.Track 6 — Field Deployment & Community Validation
- 9.About Project Sentinel
Program Overview
A multi-year open research initiative designing, building, and validating a privacy-first, fully offline edge AI platform capable of running on low-cost hardware in under-resourced environments. Project Sentinel investigates whether modular, self-healing AI infrastructure can provide meaningful network security, environmental monitoring, and community resilience for organizations — such as medical clinics, small farms, and independent businesses — that operate without dedicated IT personnel, internet dependency, or enterprise budgets.
6
Research Tracks
v1.0
Core Platform (Sep 2025)
Track 2
Currently Active
Multi-Year
2025 — Ongoing
Track Overview
Research Tracks
6 Tracks · Multi-Year (2025 — Ongoing)
Core Security Platform
Modular Architecture & Plugin System
Network Services Layer
Edge AI & On-Device Inference
IoT & Environmental Sensing
Field Deployment & Community Validation
Track 1 — Core Security Platform
The first track established the foundational security platform: a passive, offline-first network monitoring engine capable of real-time packet analysis, anomaly detection, device fingerprinting, and local threat alerting — all without requiring cloud connectivity or internet access.
Can a fully offline, locally-processed network security system running on a $100 Raspberry Pi 5 match the core detection capabilities of cloud-dependent commercial tools for small and under-resourced environments?
- Built a real-time packet capture and analysis engine using Scapy, designed for high-throughput packet processing on resource-constrained hardware.
- Developed an Isolation Forest-based anomaly detection model that learns normal baseline behavior and flags deviations without requiring labeled threat data.
- Implemented local SQLite storage with automated data retention, archival, and report generation — no external database required.
- Deployed a local web dashboard with D3.js visualizations for network activity, device inventory, alert management, and security reporting.
- Designed for cross-platform compatibility across Linux x86_64, Raspberry Pi ARM64, and macOS ARM64.
- Targeted a sub-100MB memory footprint to support viability on resource-constrained Pi 5 hardware.
- Core platform development completed September 2025, with v1.0.0 milestone marking the transition to Track 2.
Track 2 — Modular Architecture & Plugin System
Track 2 investigates the architecture of a tiered, plug-in module system that allows new research capabilities to be added to the Sentinel core without destabilizing existing functionality. This is the architectural foundation required before any of the advanced tracks can proceed.
How should a long-running, low-maintenance edge system be structured to support modular expansion over a multi-year lifecycle without requiring re-architecture or breaking core stability?
Work Completed
- Designed and implemented a Module Manager with auto-discovery via a standardized module.json schema, including tier enforcement (Lite, Pro, Elite, Ultimate).
- Established CLI commands for module lifecycle management (enable, disable, list, status).
- Architected module isolation so that individual module failure does not affect core system operation — reflecting the design principle of modules as independent, replaceable components.
Active Work
- Refining cross-module dependency enforcement and validating isolation behavior under failure conditions.
- Preparing the module system for Year 1 network services integration.
Track 3 — Network Services Layer
Track 3 extends Sentinel from a passive monitoring tool into a full local network services platform — providing the infrastructure primitives that under-resourced environments typically cannot afford or manage through commercial solutions.
Can a single $100–$200 device serve as a complete, self-managing local network authority — handling DHCP, DNS, VPN, NAS, and time synchronization — with zero ongoing maintenance requirement for non-technical operators?
Planned Modules & Research Areas
- DHCP Server — local IP management and device identity tracking.
- DNS Sinkhole (enhanced) — authoritative DNS with blocking and query logging.
- NTP Server — accurate time synchronization for logging and forensics.
- WireGuard VPN — encrypted remote access without third-party services.
- NAS Module — local encrypted file storage with SMB access and web UI.
- Certificate Manager — automated TLS certificate generation and renewal.
- Self-Healing Layer — automatic service recovery and module restart.
- UPS Monitoring — graceful shutdown and power loss handling.
Track 4 — Edge AI & On-Device Inference
Track 4 introduces hardware-accelerated, on-device machine learning inference using Intel OpenVINO — enabling Sentinel to run significantly more capable AI models without cloud processing, GPU requirements, or high-cost hardware.
What is the minimum viable hardware floor for meaningful real-time AI inference — including object detection and behavioral anomaly classification — when using OpenVINO acceleration on an Intel NUC-class device?
Planned Modules & Research Areas
- Integration of Intel OpenVINO runtime with Sentinel's existing Isolation Forest detection pipeline.
- Evaluation of OpenVINO model performance against baseline scikit-learn models on identical network traffic datasets.
- Object and person detection via camera input for physical security contexts.
- Performance profiling across hardware tiers: Pi 5 vs. SER5 vs. NUC 14 Pro.
- Documenting the AI cost curve for community-scale edge deployments.
Track 5 — IoT & Environmental Sensing
Track 5 explores Sentinel's expansion into physical environment monitoring — connecting IoT sensors and smart home/agricultural devices to the same local core that handles network security.
Can a single offline edge platform provide both network security monitoring and actionable environmental intelligence — such as soil moisture, temperature, humidity, and grow condition tracking — for small farms, greenhouses, and community agricultural sites?
Planned Modules & Research Areas
- Integration of DHT22, soil moisture, and light sensors via GPIO on Raspberry Pi 5.
- MQTT broker (Mosquitto) for low-overhead IoT device communication.
- Zigbee / Z-Wave gateway support for commercial smart sensor devices.
- Smart greenhouse module: real-time tracking of soil moisture, temperature, humidity, and light intensity with configurable alert thresholds.
- Automation rules engine: trigger actions (alerts, ventilation, irrigation signals) based on sensor conditions.
- Camera event detection for greenhouse or facility perimeter monitoring.
Track 6 — Field Deployment & Community Validation
Track 6 is the validation track — moving Sentinel from a research and development environment into real-world deployment at partner sites, including clinics, small businesses, and community agricultural facilities.
What are the real-world deployment barriers, failure modes, and support requirements for a privacy-first, offline edge AI system when operated by non-technical users in under-resourced community settings?
Planned Modules & Research Areas
- Controlled deployment at 2–3 partner sites across distinct environment types (clinic, small office, agricultural).
- Longitudinal monitoring of system uptime, alert accuracy, false positive rate, and maintenance events over 6–12 months.
- Structured user interviews with non-technical operators to evaluate usability, trust, and perceived value.
- Documentation of failure modes, recovery patterns, and self-healing effectiveness in real conditions.
- Publication of deployment findings, hardware recommendations, and a community deployment guide.
This is a living document — updated as each research track of Project Sentinel progresses.
A comprehensive field deployment report with findings and recommendations will be published upon completion of Track 6.
About Project Sentinel
Project Sentinel is built on a single design principle: a local, modular, self-healing security organism built for environments that cannot afford complexity or failure. The system is designed to run for 10–20 years without significant intervention — auto-healing failed services, auto-managing storage, and maintaining itself through modules that behave like independent, replaceable biological organs. All data stays local. No cloud. No telemetry. No vendor lock-in. Every design decision is made with one user in mind: a busy clinic manager, a small farmer, a solo business owner — someone who needs the system to just work, and never needs to understand why.
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