Smart RoombyRoom HVAC Scheduling for Residential Savings and Comfort HVAC systems account for a significant amount of the energy spent in residences with forcedair systems. Moreover, HVAC is a major contributor to greenhouse gas and fine particulate matter emissions. Recently, the use of sensors, wireless, microprocessors, and the Internet of Things (IoT) have been proposed to increase energy efficiency in residential buildings by controlling the duty cycle of furnaces and airconditioners. In this paper, we propose ILPSS (Integer Linear Programming for Smart Scheduling), a novel solution for optimizing the duty cycle of the HVAC equipment and improving usersxe2x80x99 comfort by allowing users to specify comfort levels at specific times in each room of a residence. Our proposal builds on multiplevariable, linear regression model and integer linear programming and can be run on a home IoT hub. Our experimental evaluation on a real dataset shows that our proposed solution saves energy (up to 45%) and meets usersxe2x80x99 comfort needs, compared to commodity and current smart HVAC systems.

IoT Based Architecture for Model Predictive Control of HVAC Systems in Smart Buildings The efficient management of Heating Ventilation and Air Conditioning (HVAC) systems in smart buildings is one of the main applications of the Internet of Things (IoT) paradigm. In this paper we propose an IoT based architecture for the implementation of Model Predictive Control (MPC) of HVAC systems in real environments. The considered MPC algorithm optimizes on line, in a closedloop control fashion, both the indoor thermal comfort and the related energy consumption for a single zone environment. Thanks to the proposed IoT based architecture, the sensing, control, and actuating subsystems are all connected to the Internet, and a remote interface with the HVAC control system is guaranteed to endusers. In particular, sensors and actuators communicate with a remote database server and a control unit, which provides the control actions to be actuated in the HVAC system; users can set remotely the control mode and related setpoints of the system; while comfort and environmental indices are transferred via the Internet and displayed on the endusersxe2x80x99 interface. The proposed IoT based control architecture is implemented and tested in a campus building at the Polytechnic of Bari (Italy) in a proof of concept perspective. The effectiveness of the proposed control algorithm is assessed in the real environment evaluating both the thermal comfort results and the energy savings with respect to a classical thermostat regulation approach.