Scalable Smartification of Commercial Buildings HVAC Systems using The Internet of Things and Machine Learning

EasyChair Preprint 5399

Abstract

Most of the commercial buildings in Malaysia are still equipped with the legacy control for their Heat ventilation and air conditioning system (HVAC), which several studies claimed to have contributed to energy consumption in buildings. A significant amount of this energy is consumed by the building Heat Ventilation and Air Conditioning units. This is mostly due to the lack of smart and remote functionalities in the legacy HVAC systems to control the chillers and the Air handling units. This massive energy consumption is an antithesis to what governments all over the world are aiming for. However, scalability and deployment of low-cost resource-limited hardware embedded with control algo-rithms used to save energy in commercial building’s Heat Ventilation and Air Conditioning (HVAC) units is a difficult engineering task. But the unprecedented advancement and perverseness of information technology services over the past two decades has led to an ever more connected world. This project will leverage the concept of the Internet of Energy to make the systems smarter and more de-centralized for flexible energy usage. Modern-day devices are increasingly linked to the internet, creating what is now referred to as the internet of things (IoT). The IoT paradigm has provided technologists with the ability to remotely control devices, and with the recent progress in Machine learning (ML) and Artificial Intelligence (AI), devices are trained to make smart decisions that can inde-pendently influence human to machine interactions.

Keyphrases: Artificial Intelligence, Heat Ventilation and Air Conditioning, Internet of Energy, Internet of Things, energy consumption, machine learning

@booklet{EasyChair:5399,
  author    = {Mohammed Mahdi and Taofiq Adeola Bakare and Abdul Ahmad and Adamu Muhammad Buhari and Khalid Sheikhidris Mohamed},
  title     = {Scalable Smartification of Commercial Buildings HVAC Systems using The Internet of Things and Machine Learning},
  howpublished = {EasyChair Preprint 5399},
  year      = {EasyChair, 2021}}