Intelligent Systems Using Sensors and/or Machine Learning to Mitigate Wildlife-Vehicle Collisions: A Review, Challenges, and New Perspectives

Worldwide, the persistent trend of human and animal life losses, as well as damage to properties due to wildlife-vehicle collisions (WVCs) remains a significant source of concerns for a broad range of stakeholders. To mitigate their occurrences and impact, many approaches are being adopted, with varying successes. Because of their increased versatility and increasing efficiency, Artificial Intelligence-based methods have been experiencing a significant level of adoption. The present work extensively reviews the literature on intelligent systems incorporating sensor technologies and/or machine learning methods to mitigate WVCs. Included in our review is an investigation of key factors contributing to human-wildlife conflicts, as well as a discussion of dominant state-of-the-art datasets used in the mitigation of WVCs. Our study combines a systematic review with bibliometric analysis. We find that most animal detection systems (excluding autonomous vehicles) are relying neither on state-of-the-art datasets nor on recent breakthrough machine learning approaches. We, therefore, argue that the use of the latest datasets and machine learning techniques will minimize false detection and improve model performance. In addition, the present work covers a comprehensive list of associated challenges ranging from failure to detect hotspot areas to limitations in training datasets. Future research directions identified include the design and development of algorithms for real-time animal detection systems. The latter provides a rationale for the applicability of our proposed solutions, for which we designed a continuous product development lifecycle to determine their feasibility.

"A Lightbulb Moment": Using the Theory of Planned Behavior to Explore the Challenges and Opportunities for Early Engagement of Australian Men Who Use Violence in Their Relationships

Intimate partner violence (IPV) is a common complex social and public health problem. Interventions for IPV male perpetrators are an essential component of an early and effective response. Yet little is known about how to engage men in interventions for help-seeking. Using the theory of planned behavior (TPB), we explored men's perceptions of seeking help for an unhealthy relationship and how they could be supported to recognize their behavior and undertake change at an early stage. We recruited 23 men who were currently attending a men's behavior change program in Australia to take part in focus groups. These were recorded, transcribed, and thematically analyzed. The TPB concepts of behavioral beliefs, perceived control, and subjective norms were found throughout the data. Behavioral beliefs covered four subthemes: self-awareness, self-reflection and agency, the influence of others to change, and needing the right message in the right place. Perceived control was connected to these men's understandings of what it means to be a man. Subjective norms were rarely raised, but there was some indication that men's perceptions of societal norms about men as violent influenced a perceived lack of agency to change behavior. Our findings highlight the complexity of, and challenges in, engaging men who may use violence before they reach crisis point and justice intervenes. Despite this, participating men could find acceptable an appropriately developed and easy-to-access intervention that enhances recognition of behaviors and provides links to supports. Health professionals or researchers developing early interventions targeting these men need to take the engagement challenges into account.