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@article{189389,
        author = {Kanchan and Sudha Shukla and Shrikar K.},
        title = {AI-Based Abnormal Human Activity Detection for Violent Incidents in Low-Connectivity Areas},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {5444-5452},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=189389},
        abstract = {Violent crimes like kidnappings, assaults and murders still remains a challenge in the world particularly in rural and remote areas where the infrastructure is so weak and the connectivity is so poor that the emergency response is delayed. These insecure areas are not always covered by AI-enhanced surveillance systems, despite the fact that urban spaces are becoming more susceptible to the use of AI technology. The current study suggests a surveillance camera system powered by AI, which will be used to capture abnormal human behavior including dragging, sudden falls, violent motions, or abnormal crowd behavior at any given moment. It also operates successfully even in low or no internet zones unlike traditional systems because of the use of local storage, alerts via SMS and flexible communication channels. After detecting the abnormal activity, the system sends an immediate alert to the nearest police station or a control center dedicated to control the situation. An online survey that was done using online forms offered information on how people were aware and accepted such technology. Through the elimination of connectivity barriers, this model will provide a viable measure to safer schools, hospitals, rural areas, and disaster-prone locations among other localities that struggle to access technology.},
        keywords = {Artificial Intelligence (AI), Abnormal Human Activity Detection, Surveillance System, Low-Connectivity Areas, Violence Prevention, Real-Time Monitoring.},
        month = {December},
        }