Automated Disabled People Fall Detection Using Cuckoo Search with Mobile Networks

Falls are the most common concern among older adults or disabled people who use scooters and wheelchairs. The early detection of persons’ falls is required to increase living rate an individual provide support them whenever required. In recent times, arrival Internet Things (IoT), smartphones, Artificial Intelligence (AI), wearables so on make it easy design fall mechanisms for smart homecare. current study develops Automated Disabled People Fall Detection using Cuckoo Search Optimization with Mobile Networks (ADPFD-CSOMN) model. proposed model’s major aim detect distinguish events from non-fall automatically. To attain this, presented ADPFD-CSOMN technique incorporates MobileNet model feature extraction process. Next, CSO-based hyperparameter tuning process executed model, which shows paper’s novelty. Finally, Radial Basis Function (RBF) classification recognises classifies instances as either non-fall. order validate betterment a comprehensive experimental analysis was conducted. results confirmed enhanced outcomes over other approaches accuracy 99.17%.