Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/1711 2018 2018 Department of Medical instruments engineering techniques, Alfarahidi University, Baghdad, Iraq Aymen Hussein Al-Turath University College, Baghdad, 10021, Iraq S. Ahmed Department of Computer Techniques Engineering, Mazaya University College, Thi Qar, Iraq Shorook K. Abed Accounting Department, Al-Mustaqbal University College , 51001 Hillah, Babylon , Iraq Noor Thamer Currenlty, wireless communication that is successful in the Internet of Things (IoT) must be long-lasting and self-sustaining. The integration of machine learning (ML) techniques, including deep learning (DL), has enabled IoT networks to become highly effective and self-sufficient. DL models, such as enhanced DRL (EDRL), have been developed for intelligent video surveillance (IVS) applications. Combining multiple models and optimizing fusion scores can improve fusion system design and decision-making processes. These intelligent systems for information fusion have a wide range of potential applications, including in robotics and cloud environments. Fuzzy approaches and optimization algorithms can be used to improve data fusion in multimedia applications and e-systems. The camera sensor is developing algorithms for mobile edge computing (MEC) that use action-value techniques to instruct system actions through collaborative decision-making optimization. Combining IoT and deep learning technologies to improve the overall performance of apps is a difficult task. With this strategy, designers can increase security, performance, and accuracy by more than 97.24 %, as per research observations. 2023 2023 21 34 10.54216/FPA.110202 https://www.americaspg.com/articleinfo/3/show/1711