SURVEILLANCE

The optimization of frames per second (FPS) in camera systems is a critical factor in enhancing the efficiency and reliability of modern surveillance applications. FPS directly influences image clarity, motion detection accuracy, and the overall responsiveness of monitoring systems. High FPS ensures smoother video streams, enabling precise identification of fast-moving objects, while low FPS conserves bandwidth and storage resources. This study explores the balance between performance and resource management in surveillance environments, focusing on adaptive FPS optimization techniques. Key strategies include dynamic frame rate adjustment based on scene activity, integration of artificial intelligence for motion-triggered recording, and hardware-software co-optimization to reduce latency. By aligning FPS with contextual surveillance needs—such as crowd monitoring, traffic control, and perimeter security—camera systems can achieve improved situational awareness without excessive computational or storage overhead. The findings highlight that intelligent FPS optimization not only enhances operational efficiency but also strengthens the scalability and sustainability of surveillance infrastructures.

The growing interconnection between human, animal, and environmental health has emphasized the importance of integrated surveillance systems for early detection and coordinated response to zoonotic and environmentally linked diseases. However, in many low-resource settings such as Nigeria, disease monitoring remains fragmented across sectors, resulting in delayed reporting and weak cross-sectoral collaboration. This project presents the design and implementation of a Digital One Health Surveillance (DOHS) Dashboard, a web-based system developed to unify real-time disease surveillance across the three One Health domains—human, animal, and environmental health. The system was built using a React-based frontend and a RESTful backend API, integrating modules for authentication, case management, data analytics, and geospatial visualization. HTTP polling mechanisms were implemented to achieve real-time data synchronization without requiring WebSocket infrastructure, ensuring compatibility with constrained networks. The dashboard provides role-based access control, sector-specific reporting interfaces, Excel-based data export, and an interactive GIS map powered by React-Leaflet for spatial trend analysis. Data are securely transmitted via token-authenticated API calls, while the modular architecture allows future expansion and integration with existing national systems such as SORMAS or DHIS2. Deployment was designed for both cloud-based Virtual Private Servers (VPS) and onpremise servers within health facilities, supporting continuous operation even in areas with limited internet access. The system demonstrated efficient cross-sectoral data integration, realtime monitoring of case reports, and improved accessibility for public health officers, veterinary staff, and environmental personnel. The DOHS dashboard contributes to the operationalization of the One Health approach in Nigeria by providing a scalable, adaptable, and user-friendly digital infrastructure for integrated disease surveillance. It lays the foundation for data-driven decision-making and offers a replicable model for similar low-resource environments across Africa.