Home Assistant

Modern burglar alarms use AI behavior analysis, face recognition, and seamless IoT integration. Compare Aqara, Hikvision, Frigate, and Home Assistant — with automation strategies that minimize false alarms.

Transform your Home Assistant dashboard into a PWA installable on iPhone and Android homescreens — with Service Worker offline caching, native-style push notifications, and faster load times than a full browser tab.

An FSR (Force Sensitive Resistor) network embedded in floor tiles monitors bilateral foot pressure in real-time, analyzing gait asymmetry and Center of Pressure shifts to assess fall risk in elderly residents — no wearable device needed.

Build a single Home Resilience Index score combining security threat, air quality, energy self-sufficiency, and occupant wellness dimensions — powered by HA template sensors and a real-time Lovelace gauge.

Intelligent perimeter security using Frigate NVR person detection to trigger Home Assistant outdoor lighting choreography, siren alerts, and PTZ camera pan sequences — zone by zone, fully automated.

Build a hyperlocal AQI dashboard combining personal PurpleAir sensor data, Pollution Control Department Air4Thai API, and community sensor networks to map PM2.5 at street level across Bangkok.

Train a custom Thai wake word with Porcupine and parse Thai voice commands locally with Rasa NLU to control smart home devices — all audio processing stays on-premises with zero cloud dependency.

Deploy HLK-LD2410 mmWave radar and a ballistocardiography pressure mat to monitor heart rate and respiration of elderly during sleep — no wearables required.

Unify Z-Wave, Zigbee, WiFi, and Modbus devices in a single Home Assistant instance with a real-time Energy Sankey Diagram visualizing power flow between solar, grid, home loads, and EV charger.

Build an acoustic anomaly detection system using YAMNet TensorFlow Lite on Raspberry Pi 5 to detect glass breaking, screaming, and alarm sounds, triggering Home Assistant alerts and LINE notifications.

Install SCD41 NDIR CO2 sensor to control ERV with Demand-Controlled Ventilation, maintaining CO2 below 1,000 ppm during sleep for measurable sleep quality improvement while reducing energy consumption.

Design a Demand Response automation aligned with MEA TOU electricity rates, using pre-cooling before peak hours and appliance load shifting to reduce electricity bills by 20–35% without affecting comfort.

Design a wearable fall detection system for elderly using MPU6050 IMU on ESP32 with SVM algorithm and context-aware suppression to distinguish real falls from normal sit-to-stand activity.

Design a Node-RED automation engine that learns occupancy patterns, detects conflicts between overlapping automation scenes, and resolves them automatically with full audit logging.

Deploy InsightFace on NVIDIA Jetson Nano for face-recognition gate and door control with anti-spoofing liveness detection, processing all biometric data locally without cloud transmission.

Build a sensor fusion system combining SDS011 PM2.5, BME680 TVOC, and SCD40 CO2 readings through a Kalman Filter to compute an accurate Indoor Air Quality Index with automated LINE alerts.

Build a Presence Simulation Engine on Home Assistant using randomized lighting, audio, and Markov Chain scheduling to convincingly mimic occupancy and deter burglars while away.

Design a comprehensive elderly medication management system from biometric-verified dispensing through vital sign side effect monitoring with automated physician reporting via LINE.

Detect pre-intrusion behavioral anomalies through zone loitering duration analysis, unusual vehicle parking patterns, and exterior lighting anomalies using Frigate NVR integrated with Home Assistant.

Design a smart flood and fire early warning system using Zigbee water leak sensors under sinks and washing machines, smoke detectors (Nest Protect vs Zigbee), CO detectors, and automated fire response that shuts HVAC and unlocks exit doors — with immediate LINE alerts.

Use pressure mat arrays or optical flow from cameras to analyse elderly gait — detecting gait speed below 0.8 m/s and shortened step length as early fall risk biomarkers, with a digital TUG test via Home Assistant alerting families before accidents occur.

Design a unified smart home dashboard architecture using Mosquitto MQTT broker, Node-RED for data flow, InfluxDB time-series database, and Grafana for visualisation — consolidating security, air quality, and elderly monitoring data into a single dashboard.

Design a cellular backup communicator for smart security using 4G LTE (SIM7600) and GSM (SIM800L) modules to deliver SMS/call alerts when fibre internet or Wi-Fi fails — ensuring 99.9% uptime even if an intruder cuts the line.

Use an LSTM neural network to forecast Bangkok AQI 1–4 hours ahead using IQAir API data, meteorological inputs, and seasonal patterns — proactively controlling air purifiers and ERV before PM2.5 reaches hazardous levels, reducing average exposure by 40–60%.