Abstract: This paper presents an IoT-based livestock monitoring and management system designed to improve animal health, productivity, and agricultural sustainability. Key parameters like temperature are recorded by IoT sensors on livestock that send information about their location, movement, and grazing patterns to a central platform wirelessly. The system enables real-time tracking, geo-fencing, herd safety, and early disease detection, reducing operational inefficiencies and supporting timely interventions. Machine learning algorithms further analyze the collected data to detect irregularities, predict health risks, and enhance breeding and feeding practices. Examination of historical data aids in resource allocation and emission monitoring, which supports sustainable livestock practices. By integrating IoT with intelligent analytics, the proposed system transforms conventional livestock management into a smart, automated, and data-driven approach, enhancing animal welfare and ensuring long-term agricultural sustainability.
The rapid proliferation of wireless communication devices has resulted in increasing radio-frequency (RF) activity within the 2.4 GHz Industrial, Scientific, and Medical (ISM) band. Wireless technologies such as Wi-Fi, Bluetooth, ZigBee, and numerous Internet of Things (IoT) devi…
Military operations, urban planning, environmental monitoring, and disaster management all benefit from modern aerial observation. In order to identify critical infrastructure, including airports, highways, ports, railroad stations, and defense zones, our work focuses on deep lea…
This journal presents a comprehensive study of Digital Twin Technology and its role in creating virtual replicas of physical systems for real-time monitoring, simulation, and intelligent decision-making. It discusses the architecture, working principle, enabling technologies, lif…
The use of Advanced Driver Assistance Systems (ADAS) heavily depends on the perception models to make real-time decisions but the traditional methods have tended to use specific confidence thresholds to make the trade-offs between missed detections and false alarms to be not opti…
Artificial intelligence (AI) in modern healthcare is one of the most transformational technologies available, giving unparalleled prospects to advance preventative medicine and treat chronic diseases. AI enhances healthcare systems’ ability to identify diseases earlier, predict h…
This concept note presents a concise authorial statement of selected foundational propositions of Dynamic Semantic ER, an original framework for observing how Meaning arises, changes state, and may undergo Structural Update within a Meaning Field. The note introduces the central…