Abstract
The critical requirements for devices connected to the Internet of Things are long battery life, long coverage range, and low deployment cost. The authors developed a machine-learning-based smart controller for a commercial buildings HVAC (heating, ventilation, and air conditioning) system using LoRa (a long-range, low-power wireless platform) and compared it with short-range RF communication in an indoor setting. Results show that LoRas coverage range was 60.4 percent more than short-range communication inside the building. The smart controller was capable of identifying when a room was unoccupied and turning off the HVAC, reducing its energy consumption up to 19.8 percent.
| Original language | English |
|---|---|
| Pages (from-to) | 30-38 |
| Number of pages | 9 |
| Journal | IT Professional |
| Volume | 20 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - Oct 2018 |
Keywords
- energy consumption
- commercial building
- IoT
- Internet of Things
- HVAC
- reducing energy consumption
- LoRa
- smart controller
- Internet of Things
- machine learning
- artificial intelligence
Documents and Links
- Javed, A. et al (2018) Improving Energy Consumption of a Commercial Building with IoT and Machine Learning
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