INTRODUCTION
Farmerβs clashes among Fulani herdsmen and host communities often result as when grazing cattle are not properly controlled and consequently graze on cultivated plants like melon, okora, beans, cassava, maize to mention but few etc. in farmlands of host communities. Efforts farmers to register their objection of destruction of their livelihood (food crops and cash crops) by the cattle of Fulani herdsmen are always stoutly resisted thereby degenerating into clashes. Host communities sometimes register their grievances by placing restrictions on movement and gracing of cattle in designated areas and enforcing compliance through coercive measures decreed by the host community vigilante which may take the shape of killing stray cattle or arresting and prosecution defaulters.
Fulani herdsmen and farmers crisis no doubt have negative impact on the lives, property, food security and educational development in Nigeria. Though, there is the dearth of quantitative evaluation of the catastrophic attacks, available statistics has it that between June 2015 to December, 2016 Human Rights Watch in 2017, reported a total death toll of 65 persons in more than 24 attacks. It was also reported that an estimate of 50 people were killed in Nasarawa Egor (Nasarawa State) and Agatu/Logo (Benue State) in the June 2016 and recently lives were claimed in Abraka in the April 23 rd 2017 crisis between Fulani herdsmen and farmers. Fulani herdsmen attack apart from the loss of lives has also led to the destruction of arable farmland and valuable properties worth several billions of naira.
π Over 50,000 Project Materials
π± 100% Offline: No internet needed
π Over 98 Departments
π Software coding and Machine construction
π Postgraduate/Undergraduate Research works
π₯ Instant Whatsapp/Email Delivery
The project topic, "Predicting Disease Outbreaks Using Machine Learning and Data Analysis," focuses on utilizing advanced computational techniques to ...
The project on "Implementation of a Real-Time Facial Recognition System using Deep Learning Techniques" aims to develop a sophisticated system that ca...
The project topic "Applying Machine Learning for Network Intrusion Detection" focuses on utilizing machine learning algorithms to enhance the detectio...
The project topic "Analyzing and Improving Machine Learning Model Performance Using Explainable AI Techniques" focuses on enhancing the effectiveness ...
The project topic "Applying Machine Learning Algorithms for Predicting Stock Market Trends" revolves around the application of cutting-edge machine le...
The project topic, "Application of Machine Learning for Predictive Maintenance in Industrial IoT Systems," focuses on the integration of machine learn...
Anomaly detection in Internet of Things (IoT) networks using machine learning algorithms is a critical research area that aims to enhance the security and effic...
Anomaly detection in network traffic using machine learning algorithms is a crucial aspect of cybersecurity that aims to identify unusual patterns or behaviors ...
Predictive maintenance is a proactive maintenance strategy that aims to predict equipment failures before they occur, thereby reducing downtime and maintenance ...