Putting technology between people and tigers

In 2010, during a St. Petersburg summit on tigers, 13 tiger range countries agreed to double the global population by 2022. As result, long-term coordinated efforts have been implemented recover populations, including controlling illegal trade of protecting and restoring habitat movement corridors, patrolling against poaching. Local people pivotal conservation across states (Wikramanayake et al., 2010). An estimated 1737 tigers added since 2010 in four (i.e. India, Nepal, Russia, Bhutan; Supporting Information). These gains are good news for conservation, but they risk being undermined if potential increased human-tiger conflict is not managed (Acharya 2016). Deaths injuries due attacks at high level several (Supporting Much South Asia close areas with highest human densities world, coupled growth rapid urbanization (CIESIN, 2018). require large areas, growing it anticipated that there could be greater conflict. Management dangerous life requires identification, capture, rehabilitation problem individuals, which often difficult, time-consuming, expensive. Identification such animals deployment intensive camera trap arrays (NTCA, 2013), manual retrieval processing data. Furthermore, may mix non-problem ones, making differentiation between two lengthy complex process 2013). Lengthy delays reporting capture increase chances further escalation conflicts. Other methods like electric fencing, prevent trespassing, can expensive, insufficient, fatal (The Hindu, 2017). Governments compensation payments provide economic support victims' families garner positive attitudes toward their (Karanth, Gupta & Vanamamalai, 2018; DNPWC, 2019). This is, however, too slow lag communication bureaucratic processes 2018), clearly inadequate proactively mitigating We believe new technology offers great reducing For example, automated systems integrating high-resolution imaging sensors, wireless technology, artificial intelligence (AI) (Norouzzadeh 2018) used rapidly detect, identify, track, warn presence. enable real-time data notification capabilities, thus significantly time lags detection action. They also useful helping managers forecast respond immediately effectively. Developments already taking place. mobile sensor images, AI detect identify from transmission information over network animal presence show human-elephant Thailand (Mongabay, 2020). addition, centralized application allows local community members submit behavior Mobile applications would make convenient report, communicate, track conflicts compensation, as open-source Wild Seve India (Karanth technologies non-imaging sensors (Kamminga notify intrusions. Such cheaper, cover warnings, giving locals chance prepare respond. Non-lethal deterrents fox lights deter leopards (Naha 2020), pumas Chile (Ohrens, Bonacic Treves, 2019), ultrasonic repellents cats Australia (Crawford, Fontaine Calver, LED flashlights Kenya lions (Lesilau promising approach management. Currently, underutilized Asia. costs involved implementing infrastructure training personnel, reluctance adopt or perceived uncertainty its effectiveness. Investment mitigate through likely far more cost effective than traditional approaches. If collaborate research development, reduced. New knowledge integration employment opportunities an advantage. While increasing populations utmost importance, this should come expense countries. Greater test proactive needed help live alongside maintain conservation. building testing using shared databases within cloud computing frameworks implement analytics, prediction, mining offer preventing Open access publishing facilitated RMIT University, Melbourne, VIC, part Wiley – agreement via Council Australian University Librarians. Appendix S1. Data cases. Please note: The publisher responsible content functionality any supporting supplied authors. Any queries (other missing content) directed corresponding author article.