Artificial Intelligence-Assisted Energy and Thermal Comfort Control for Sustainable Buildings: An Extended Representation of the Systematic Review Ghezlane Halhoul Merabet 1, 9* , Mohamed Essaaidi 1 , Mohamed Ben-Haddou 2 , Basheer Qolomany 3 , Junaid Qadir 4 , Muhammad Anan 7 , Ala Al-Fuqaha 5, 6 , Riduan Mohamed Abid 8 and Driss Benhaddou 9 1 Smart Systems Laboratory (SSL), ENSIAS, Mohammed V University of Rabat, 713 Morocco 2 MENTIS SA, 13, rue de Congrès, 1000 Brussels, Belgium 3 Department of Cyber Systems, College of Business and Technology, University of Nebraska at Kearney (UNK), Kearney, NE 68849, USA 4 Information Technology University, Lahore 54000, Pakistan 5 Information and Computing Technology (ICT) Division, College of Science and Engineering (CSE), Hamad Bin Khalifa University, Doha – Qatar 6 Department of Computer Science, Western Michigan University, Kalamazoo, MI 49008, USA 7 Software Engineering Department, Alfaisal University-Riyadh, Saudi Arabi 8 School of Science and Engineering, Alakhawayn University in Ifrane, 1005, Ifrane, Morocco 9 Department of Engineering Technology, University of Houston, TX 77204, USA Abstract – Discussion of the environmental impact of buildings has been gaining weight in the agendas of a number of cities and countries around the world. Indeed, approximately 38% of the final energy consumption growth between 2015 and 2050 in the world is correlated to the use and occupation of buildings. In this regard, the building sector was identified as a leading contributor to global production of CO2 in the fifth report produced by the International Panel of Climate Change (IPCC) [1]. However, the same report also has identified this sector as the one with the greatest potential for reducing CO2 emissions through design opportunities, technological advances, and user behavior. Nowadays, research has been directed towards more advanced control structures that take multiple inputs (temperature, humidity, comfort sensation, etc.) and uses artificial intelligence (AI) techniques for heating, ventilation, and air-conditioning (HVAC) control, design, management, optimization, and maintenance. This paper performs a systematic review in order to investigate the use of AI-based tools for improving the performance of energy control systems and enhance thermal comfort. This enables a holistic understanding of (1) the challenges of providing thermal comfort to the users inside buildings in an energy efficient way, and (2) the related bibliographic material to help researchers and professionals in the area undertaking such a challenge. Compared to existing reviews, this paper extends the state of the art by reviewing and categorizing all existing publications and providing the material related to the AI-assisted tools for building environment control while considering a dynamic interaction within comfort- subject-energy control loop. Keywords – Buildings; Occupants; Control; Thermal comfort; Energy savings; Artificial intelligence; Machine learning; Heating Ventilation and Air-Conditioning (HVAC) systems; Systematic literature review