A Context-Driven Approach using IoT and Big Data Technologies for Controlling HVAC Systems

This approach is designed to minimize energy consumption while maintaining occupants' comfort. The performance of the proposed control was evaluated in a real test site by deploying a control card that links the controller with the HVAC system. A smart application for real-time feedback control was also developed and deployed to dynamically adapt the controller to context changes. The HVAC system is composed of equipment that controls the indoor air temperature and airflow in a considered space. The indoor air temperature is based mainly on the outside temperature with the heating or cooling schedule together with the number of occupants in the controlled space. The proposed control approach takes into consideration additional parameters to further reduce energy consumption while improving occupants' thermal comfort. The proposed state feedback control approach allows a linearization of the thermal system building equations to convert a bilinear system into a linear system. The thermal state feedback control deployed in the control card regulates the indoor air temperature based on the desired temperature, the equation used is given as follows: u = -K * (T - Td) Where the parameters are as follows: T is a derived vector from temperature, Td is a temperature vector, u is an input vector, K is a gain matrix, and T is an output vector. In our case, the input vector u is used to regulate the variation of the fan rate in order to gather the required temperature's comfort. The proposed control approach was evaluated in a real test site by deploying a control card that links the controller with the HVAC system. A smart application for real-time feedback control was also developed and deployed to dynamically adapt the controller to context changes. Experimental results show that the proposed state-feedback control outperforms the PI and ON-OFF approaches in terms of energy consumption while providing acceptable thermal comfort. The proposed control approach has several advantages, including the ability to minimize energy consumption while maintaining occupants' comfort. The approach also allows for real-time feedback control and dynamic adaptation to context changes. The proposed control approach can be applied to various types of HVAC systems and can be integrated with existing building management systems. The proposed control approach has been evaluated in a real test site and has shown promising results. The approach has the potential to be widely adopted in the building industry, particularly in energy-efficient buildings. The proposed control approach can be further improved by incorporating additional parameters and by developing more advanced control algorithms. The proposed control approach can be applied to various types of HVAC systems, including air-conditioning and heating systems. The approach can be integrated with existing building management systems and can be used to control multiple HVAC systems in a building. The proposed control approach can also be used to control other types of building systems, such as lighting and shading systems. The proposed control approach has several potential applications, including energy-efficient buildings, smart homes, and commercial buildings. The approach can be used to minimize energy consumption while maintaining occupants' comfort, which can lead to significant cost savings and reduced environmental impact. The proposed control approach can also be used to improve the overall performance of HVAC systems and to enhance the comfort and well-being of building occupants.