Author(s):
1. Abid Yahya:
Botswana International University of Science and Technology (BIUST),Botswana
Abstract:
Foot-and-Mouth Disease (FMD) poses a persistent threat to Botswana's livestock sector. This keynote presents a sensor-enabled, machine learning (ML) and statistical modeling framework for enhanced FMD surveillance and control. Sensor networks capture real- time data on livestock movement, environmental factors, and health indicators, which are analyzed using ML algorithms and geo statistical methods to detect hotspots, forecast outbreaks, and guide targeted interventions. The approach improves early detection accuracy, optimizes vaccination and movement control strategies, and supports proactive, datadriven decision-making for sustainable livestock management and national biosecurity.
Page(s):
39-39
DOI:
DOI not available
Published:
Journal: 4th International Conference of Sciences “Revamped Scientific Outlook of 21st Century, 2025” , November 12,2025, Volume: 1, Issue: 1, Year: 2025
Keywords:
machine learning
,
Accuracy
,
FMD
,
sensor networks
,
Statistical Modeling
References:
References are not available for this document.
Citations
Citations are not available for this document.