Occupancy & Indoor Air Quality Monitoring for a Small Office Building

The client manages a modern, three-story commercial office building. They wanted to improve tenant comfort and cut energy waste, but they lacked the necessary data. Their main problems included:

• Inconsistent Thermal Comfort. Tenants often complained that rooms were too hot or too cold. This was frequently because the heating, ventilation, and air conditioning (HVAC) system ran on fixed schedules, ignoring the actual occupancy or needs of the room.
• Poor Indoor Air Quality (IAQ). Due to limited ventilation control, CO2 levels in meeting rooms became high during peak use. This resulted in lower staff productivity and physical discomfort, such as drowsiness or headaches.
• Inefficient Space Utilization. Management had no clear data on how frequently meeting rooms or common areas were actually used. This made it difficult to optimize cleaning schedules, reduce energy consumption, or plan future layout changes.
• Energy Waste in Unused Spaces. The HVAC and lighting systems frequently continued running at full power in empty areas, causing unnecessary energy consumption and increasing costs.

Our team developed a focused Occupancy and Indoor Air Quality (IAQ) Monitoring Solution using ThingsBoard. The solution was designed for fast deployment and to deliver immediate, useful insights within a strict budget. We integrated with the client's chosen off-the-shelf sensors (e.g., multi-sensors tracking CO2, temperature, and basic presence). The solution included:

1. ThingsBoard as the Core Platform. We configured the ThingsBoard Community Edition to be the central hub for all building sensor data, processing logic, and visualization.
2. Data Ingestion Layer. We set up standard MQTT and/or HTTP integrations to take in data from the client's IAQ sensors (CO2, Temperature, Humidity) and occupancy sensors installed in meeting rooms, common areas, and open offices.
3. Building Asset Management. We logically mapped the building within ThingsBoard, creating 'Assets' for the building, each floor, and individual rooms, linking all necessary sensors ('Devices') to these assets.
4. Essential Rule Engine for Insights & Alerts: We configured ThingsBoard Rule Chains to monitor the incoming data and provide value:

• • Occupancy Insight: Processing raw presence data into clear status indicators (e.g., "Room 101: Occupied/Vacant").
  • IAQ Health Check: Setting dynamic thresholds for CO2 levels (e.g., sending an alert if CO2 exceeds 1000 ppm).
  • Comfort Monitoring: Alerting management if the temperature goes outside the set range during working hours.

5. User-Friendly Monitoring Dashboard: We created a single, targeted dashboard in ThingsBoard for the facility manager, which displayed:

• • Real-time IAQ status (CO2, Temp) for all monitored rooms (using easy-to-read color codes).
  • Live occupancy status and graphs showing historical utilization trends (room usage hours per day/week).
  • A clear record of all high CO2 or temperature deviation alerts.

6. Data Intelligence and Reporting. The system automatically saved all data, allowing the client to generate basic reports on how often rooms were used and the average IAQ scores.

1. 10% Reduction in HVAC Energy Costs. By seeing the actual room usage, the facility manager could adjust the HVAC system’s schedules, ensuring that heating and cooling were reduced or turned off in areas confirmed to be empty, especially during evenings and weekends.
2. Improved Meeting Room Productivity. Real-time CO2 monitoring resulted in quick manual adjustments to ventilation (and provided justification for future automated upgrades). Management now acts proactively when CO2 rises, reducing staff drowsiness and improving focus.
3. Increase in Meeting Room Utilization Transparency: Accurate usage data highlighted which meeting rooms were overbooked and which were underused. This allowed management to update the booking policy and justify a future layout change to better distribute space.
4. Reduction in Tenant Complaints: The ability to immediately view and confirm environmental conditions (e.g., "Room 205 is currently 22.5°C, which is within the target range") and quickly address poor air quality led to a noticeable drop in comfort-related complaints.
5. Data-Driven Cleaning Schedules: Usage metrics were employed to optimize cleaning schedules, moving resources away from underused areas and focusing more attention on high-traffic or poorly ventilated rooms, increasing overall operational efficiency.