International Journal of Advances in Applied Computational Intelligence
Journal DOI
2833-5600ISSN (Online)
Volume 5 , Issue 2 , PP: 24-33, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Taher Ahmed Jubbori 1 , Ahmad Khaldi 2 , Karla Zayood 3
Doi: https://doi.org/10.54216/IJAACI.050202
Social isolation and loneliness are subjective measures related to the feeling of distress and discomfort for disabled and elderly people. Currently, computing platform offers a smart healthcare observing technique for earlier fall detection. Internet of Things (IoT) based health system had a crucial role in the healthcare service and assists in improving data processing and its prediction. Transmitting data or reports takes more energy and time, as well as causes energy issues and higher latency. These study concentrations on the development of Whale Optimization Algorithm with Deep Learning based Indoor Monitoring System (WOADL-IMS) for Elderly and Disabled People. The presented WOADL-IMS system purposes to identify the presence of indoor activity by elderly people. In the presented WOADL-IMS technique, NASNetMobile model is applied to produce feature vectors. In addition, the WOADL-IMS technique uses WOA based hyperparameter selection approach. Finally, triplet neural network (TNN) model can be employed for automated classification and recognition of indoor activity. The simulation result of the WOADL-IMS approach can be examined on indoor activity dataset. The outcomes of the experimentation highlighted that the WOADL-IMS technique reaches better results than other recent approaches
Indoor activity monitoring , Elderly and disabled person , Deep learning , Whale optimization algorithm
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