Iman Bagheri - Department of Biomedical Engineering, Imam Reza International University,Mashhad, Iran
Ashraf Mohammadzadeh - Department of Business Administration - International Business, KheradgerayanMotahar Institute of Higher Education, Mashhad, Iran
Melika Hemmatian - Department of Psychology, Salman Institute of Higher Education, Mashhad, Iran
Ammar Azzawi, - Department of Psychology, Ferdowsi University of Mashhad
Kaveh Torabi - Architectural Engineering, Bahar Ab Oshtorankouh Co, Khoramabad, Iran,
Ahad Alvandi, - Department of Electrical and Computer Engineering, Kharazmi University, Tehran,Iran

Internet of Things has always been the main focus of interest for many applications, including lowpower systems, monitoring, and STEM applications, particularly for mandatory wireless datatransmission. The aforesaid technology is relatively new concerning forms the backbone of industrywhere multiple applications can be defined where management approaches are necessary to beconsidered in these wide areas of usage—ranging from applications where psychologist and doctorscan use their digital questionnaires regarding their patients monitoring for vital signals to applicationswhere accusers in courts can be monitored remotely and precisely regarding official oath to evenengineering applications in different STEM branches, namely as biomedical and electrical applications.There are also some more of the aforementioned applications where engineers can take advantage ofsmart systems for their ۳D scanning for architectural engineers, bio-related information regardingsmart data transmission, and other purposes where IoT can have a significant role by definition.Considering Machines learning through the Internet of Things system allows for the use of approacheswhere management efficient communications between machines based on intelligence judgments canbe performed. The paper's novelty is to combine deep learning and the Internet of Things to regulate the functioning of wide applications and provide our recent effort with a design-based approach. As a result, such a smart system can facilitate the applications where IoT has not been applied and increases the chances of working smarter and more intelligently regarding efficiency, power consumption, and user performance. The suggested approach improves energy consumption decision-making, and regarding the intensive test scenarios implemented in this research, a specific smart system is also suggested to confirm the efficiency and effectiveness of the provided system.

Management, Internet of Things, Behavioral and Cognitive Approaches, STEM Branch Applications, Machine Learning