Human–wildlife conflict and technological mitigation strategies: a systematic review

Abstract

The conflict between human and wildlife is called human–wildlife conflict (HWC). This poses a major obstacle to conservation and to human safety. Following PRISMA 2020 guidelines, this systematic review aimed to explore HWC incidents, contributing factors, mitigation, and technological interventions. The collected information is analyzed for the main categories of conflict, involvement of species, mitigation results, and effectiveness of technological solutions. The results indicated that crop raiding, depredation on livestock, and human attack were the most reported HWC incidents and the most involved species are elephants, tigers, monkeys, and crocodiles. Strong governance, agriculture expansion, habitat fragmentation, and settlement by humans are identified as the major contributors to HWC. The review also confirmed that technological solutions, such as artificial intelligence (AI), deep learning, and machine learning, had positive impacts on the detection, tracking, generation of early warnings, and prediction of conflicts with wildlife. The results of the meta-analysis showed that deep learning techniques had the highest technological effectiveness, 0.83, followed by machine learning (0.76), AI-based systems (0.72), and sensor-based technologies (0.58). The review finds integrated approaches to HWC mitigation using advanced technologies, ecological conservation, and community engagement are the most sustainable ways to minimize HWC and ensure long-term human–wildlife coexistence.