InfluxDB

Home Assistant is an open-source Smart Home platform supporting Philips Hue, Xiaomi, Google Nest, and 3,000+ brands with powerful automation, InfluxDB data logging, and full local privacy control.

Home Assistant offers advantages over other Smart Home platforms — complete privacy, full control, support for 3,000+ brands, and complex automation with no subscription fees.

Modern smart homes go beyond convenience — they become comprehensive family health care systems, from air quality detection and sleep tracking to emergency alerts for elderly members.

Connecting Smart Home with a Fresh Air System requires the right strategy. This article explains IoT integration step by step — from building a sensor network and defining automation rules to using AI to optimize the system around your family's patterns.

Smart home technology manages PM2.5 end-to-end: real-time sensors, HEPA+UV-C purifiers, positive pressure ventilation, and AI pattern analysis — all connected to Home Assistant for unified automatic control.

Turn indoor air quality data into actionable insights with Grafana dashboards for long-term trend analysis, predictive filter replacement scheduling, and correlation with outdoor AQI data.

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

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.

A Smart Caregiver Dashboard centralizes all elderly resident health data into a single IoT platform, giving professional caregivers real-time access to vitals and activity logs while families receive morning summary reports via LINE OA—coordinating professional and family care without redundant monitoring.

A Living Digital Twin connects the BIM model bidirectionally with live IoT sensor data—making the 3D building model reflect real-world conditions at every moment, detecting deviations from design intent, and enabling continuous system optimization throughout the building’s operational lifetime.