Epidemiology of Lumpy Skin Disease in Cattle: Prevalence, Risk Factors, and Implications for Control in Karachi, Pakistan

Imran khan jatoi; Mushtaque Ahmed Rahu; Nimra Memon; Muhammad Aurangzaib; Urooj Oad

Epidemiology of Lumpy Skin Disease in Cattle

Prevalence, Risk Factors, and Implications for Control in Karachi, Pakistan

Authors

Imran khan jatoi Department of Statistics, Shaheed Benazir Bhutto University, Shaheed Benazirabad, Pakistan
Mushtaque Ahmed Rahu PhD, Department of Electronic Engineering, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah, Pakistan
Nimra Memon Department of Computer Science, Govt Girls Degree College, Nawab Shah, Pakistan
Muhammad Aurangzaib Department of Cybersecurity, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah, Pakistan,
Urooj Oad MS Scholar, College of Graduate and Professional Studies, Trine University, Angola, Indiana, USA

Keywords:

AI, IoT, Digital Twins, smart farming, climate resilience

Abstract

The effects of climate change on agriculture are very profound, including food security and the financial stability of developing countries. Thus, Artificial Intelligence (AI), Internet of Things (IoT), and Digital Twins (DTs) are significant in changing agriculture to a data-enabling, real-time system to develop crop management, high productivity, and climate mitigation. Such technologies are useful in predicting the time of droughts and scheduling the irrigation timetable based on climatic changes, and also in deciding on the appropriate crop rotation within a particular area. AI and IoT may be combined to create DTs to facilitate climate-resilient precision farming. This technology embraces agricultural workplaces, livestock surveillance, crop harvesting, crop protection, and predictive maintenance systems. It also changes how agriculture is practised by examining huge amounts of information to predict the impact of climate change. Precision agriculture is an AI-driven technology that uses micro-localised applications, which are informed by synthetic sensory data, drones, and satellite data. Whereas Smart agriculture combines AI, Big Data Analytics, IoT, and DT to collect, unite, and interpret information from many sources. With AI-powered models, future weather conditions, insects, and disease outbreaks are predictable, allowing for early intervention and increased crop production. Such insights culminate in better allocation of resources, optimisation of agricultural activities, and high farm productivity amidst climate change. As a consequence, the DT technology can be a game-changer in the field of agriculture in the future. In this study, DT in conjunction with IoT sensors and AI models has been explained conceptually and potentially as useful in precision agriculture to adjust to the rise in climate change by anticipating droughts, optimising irrigation, and enhancing crop control through real-time data analysis.

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Epidemiology of Lumpy Skin Disease in Cattle