Journal of Intelligent Systems and Internet of Things JISIoT 2690-6791 2769-786X 10.54216/JISIoT https://www.americaspg.com/journals/show/743 2019 2019 Department of Biomedical Engineering, VelTech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College, Chennai, India Gopinath Gopinath Department of Biomedical Engineering, VelTech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College, Chennai, India. Kirubasri G. G.V. Department of Biomedical Engineering, VelTech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College, Chennai, India Haritha Sasikumar Department of Biomedical Engineering, VelTech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College, Chennai, India Yazhini .. Department of Biomedical Engineering,L.D. College of Engineering, Ahmedabad.India Jagruti Patil Bharath Institute of Higher Education and Research,Chennai, India Gopinath Gopinath A fall of an older adult often leads to severe injuries and is found to be a significant reason for the death due to post-traumatic complications. Many falls happen in the home atmosphere and prevail unrecognized. Thus, the need for reliable early fall detection is necessary for fast help. Lately, the emergence of wearables, smartphones, IoT, etc., made it possible to develop systems fall detection which aids in the remote monitoring of the elderly. The goal is to allow intelligent algorithms and smartphones to detect falls for elderly care and to monitor them regularly. This work presents the Artificial Intelligence of Things for Fall Detection (AIOTFD) system using a slime mould algorithm (SMA) to optimize the final data. The features extracted using SqueezeNet further CNN based SMA used for data optimization. The validation of the AIOTFD model performance is evaluated through the Multiple Cameras Fall Dataset (MCFD) and UR Fall Detection dataset (URFD). The empirical results accentuated the assuring realization of the model compared to other state-of the art methods.The obtained results shows our proposed AIOTFD attains accuracy of 99.82% and 99.79% and databases can be used for additional investigation and optimizations to increase the recognition rate to enhance the independent life of the elderly. 2021 2021 18 31 10.54216/JISIoT.030102 https://www.americaspg.com/articleinfo/18/show/743