Smart Building IoT Sensors & Analytics
Real-time visibility of occupancy, energy, air quality and asset performance through wireless sensor networks and cloud analytics.
Beyond Traditional BMS
Building Management Systems excel at plant control but provide limited visibility into occupant experience, space utilisation, and granular energy consumption. Traditional BMS sensors are expensive to install, difficult to expand, and focused on mechanical systems rather than people.
Smart building IoT systems use wireless sensors, cloud analytics, and machine learning to monitor conditions that traditional BMS cannot economically address—desk occupancy, meeting room utilisation, localised air quality, equipment health, and tenant-specific energy consumption. This data enables demand-based HVAC control, space optimisation, and predictive maintenance, delivering operational savings and improved occupant comfort.
IoT Sensor Applications
Occupancy Monitoring
Wireless PIR, CO₂, and desk sensors track room and desk utilisation in real-time. This data enables demand-based HVAC (reducing heating/cooling in unoccupied zones), space planning (identifying underutilised areas), and cleaning optimisation (scheduling based on actual use). Typical occupancy rates in commercial offices are 40-60%—right-sizing HVAC to actual occupancy reduces energy consumption by 20-30%.
Indoor Air Quality (IAQ) Sensors
CO₂, VOC, PM2.5, temperature and humidity sensors monitor air quality at desk level. Poor IAQ causes occupant complaints, productivity loss, and sick building syndrome. Real-time IAQ data enables automated ventilation adjustments (increasing fresh air when CO₂ rises) and identifies problem zones (poor airflow, contamination sources). Post-pandemic, IAQ visibility has become essential for occupant confidence and ESG reporting.
Energy Submetering
Clamp-on CT sensors monitor electricity consumption at circuit level without building downtime. This enables tenant billing accuracy, identification of energy-wasting equipment (printers left on, inefficient servers), and validation of energy-saving measures. Multi-tenant buildings benefit most—submetering allows fair cost allocation and incentivises tenant energy efficiency. ESOS and SECR reporting also benefit from granular consumption data.
Predictive Maintenance Sensors
Vibration, temperature, and current sensors monitor mechanical plant health. Abnormal vibration indicates bearing wear, temperature spikes suggest lubrication failure, and current anomalies reveal motor degradation. Early detection prevents catastrophic failures—replacing a bearing costs £500, replacing a failed motor costs £10,000+. Predictive maintenance reduces reactive callouts by 30-50% and extends asset life by 15-25%.
Water Leak Detection
Moisture sensors and flow meters detect leaks in plant rooms, risers, and toilets. Early detection prevents water damage (insurance claims averaging £50,000+), reduces water waste, and protects sensitive equipment. Sensors are typically installed at high-risk locations (below pipes, in plant rooms, under water heaters). Alerts are sent to facilities teams within seconds of detection.
Cloud Analytics & Dashboards
Data from wireless sensors is aggregated in cloud platforms (Azure IoT Hub, AWS IoT Core, Google IoT) and visualised through dashboards accessible via web and mobile. Machine learning algorithms identify trends, anomalies, and optimisation opportunities. Automated alerts notify facilities teams of abnormal conditions—high CO₂, equipment failure, water leaks. Dashboards provide portfolio-level visibility for multi-site estates.
Wireless Sensor Technologies
LoRaWAN (Long Range Wide Area Network)
Low-power, long-range wireless protocol. Single gateway covers 2-5km range (urban) or 15km+ (rural). Battery life 5-10 years. Ideal for campus estates, industrial sites, and multi-building portfolios. Lower bandwidth than WiFi but excellent for periodic data (temperature, occupancy).
Zigbee / Z-Wave
Mesh networking protocols—sensors relay data through neighbouring devices, extending range without additional gateways. Range 10-100m per hop. Battery life 1-5 years. Ideal for dense sensor networks (offices, hotels). Higher bandwidth than LoRaWAN but shorter range.
NB-IoT / LTE-M (Cellular)
Cellular-based IoT protocols. No gateway required—sensors communicate directly to cloud via mobile networks. Ideal for remote sites without local network infrastructure. Higher operating cost (SIM data charges) but unmatched reliability and coverage. Battery life 5-10 years.
WiFi / Ethernet
Mains-powered sensors connected to existing IT infrastructure. High bandwidth, real-time data, but requires power and cabling. Suitable for high-value applications (air quality monitoring in labs, critical equipment monitoring). No battery constraints but higher installation cost.
Real-World ROI Examples
Corporate Office, Manchester (10,000m²)
Deployment: 200 occupancy sensors, 50 IAQ sensors, 20 energy submeters
Findings: 45% desk utilisation, 30% meeting room utilisation, 25% HVAC over-ventilation
Actions: Implemented hot-desking (reduced leased space by 2,000m²), demand-based HVAC
Result: £180,000 annual saving (rent + energy), 18-month payback
Industrial Warehouse, Birmingham (50,000m²)
Deployment: 100 temperature sensors, 30 vibration sensors (motors), 10 water leak sensors
Findings: 3 motors showing abnormal vibration, 1 water leak in plant room (undetected)
Actions: Replaced bearings on 3 motors (£1,500), repaired water leak (£800)
Result: Prevented 3 motor failures (£30,000+ saved), avoided water damage (£50,000+ claim)
Multi-Tenant Office, London (15,000m²)
Deployment: Energy submetering (30 circuits), IAQ sensors (100 locations)
Findings: One tenant consuming 40% more energy than similar-sized tenants
Actions: Implemented accurate tenant billing, provided energy usage dashboards
Result: Fair cost allocation, tenant energy reduction of 15% (behavioural change from visibility)
Integration with Existing Systems
IoT systems integrate with BMS, lighting controls, access control, and energy management systems through open protocols (BACnet, Modbus, MQTT). This enables automated responses—reducing HVAC in unoccupied zones, dimming lights when daylight is sufficient, adjusting ventilation based on CO₂ levels.
Data can also feed into CAFM systems (Computer-Aided Facilities Management) for maintenance scheduling, helpdesk systems for automated ticket creation, and ESG reporting platforms for carbon and energy tracking. The goal is actionable intelligence, not just data collection.
Related Services
Request IoT Assessment
Our team designs and installs wireless IoT sensor networks for commercial, industrial, and public sector estates. We provide turnkey solutions including sensor hardware, cloud platforms, analytics, and ongoing support. Contact us for a site-specific IoT proposal.
Request IoT Assessment