Putting technology between people and tigers

In 2010, during a St. Petersburg summit on tigers, 13 tiger range countries agreed to double the global tiger population by 2022. As a result, long-term coordinated efforts have been implemented to recover tiger populations, including controlling the illegal trade of tigers, protecting and restoring habitat and movement corridors, and patrolling against poaching. Local people have been pivotal to tiger conservation efforts across the tiger range states (Wikramanayake et al., 2010). An estimated 1737 tigers have been added to the global tiger population since 2010 in four of the 13 tiger range countries (i.e. India, Nepal, Russia, and Bhutan; Supporting Information). These gains are good news for tiger conservation, but they risk being undermined if the potential for increased human-tiger conflict is not managed (Acharya et al., 2016). Deaths and injuries due to tiger attacks are at a high level in several countries (Supporting Information). Much of the tiger habitat in South Asia is close to areas with the highest human population densities in the world, coupled with high population growth and rapid urbanization (CIESIN, 2018). As tigers require large areas, with growing human and tiger populations, it is anticipated that there could be greater potential for conflict. Management of tigers that are dangerous to human life requires the identification, capture, and rehabilitation of problem individuals, which is often difficult, time-consuming, and expensive. Identification of such animals requires the deployment of intensive camera trap arrays (NTCA, 2013), and often manual retrieval and processing of data. Furthermore, such animals may mix with non-problem ones, making the differentiation between the two lengthy and complex process (NTCA, 2013). Lengthy delays between reporting and capture of animals increase the chances of further escalation of conflicts. Other methods like electric fencing, to prevent trespassing, can be expensive, insufficient, and are often fatal to tigers (The Hindu, 2017). Governments have implemented compensation payments in several countries to provide economic support to victims’ families and to garner positive attitudes toward tigers and their conservation (Karanth, Gupta & Vanamamalai, 2018; DNPWC, 2019). This is, however, often too slow due to a lag in communication and bureaucratic processes (Karanth, Gupta & Vanamamalai, 2018), and clearly is inadequate for proactively mitigating conflicts. We believe new technology offers great potential for reducing human-tiger conflicts. For example, automated systems integrating high-resolution imaging sensors, wireless technology, and artificial intelligence (AI) (Norouzzadeh et al., 2018) could be used to rapidly detect, identify, track, and warn of tiger presence. These systems enable real-time data processing and notification capabilities, thus significantly reducing time lags in detection and action. They can also be useful for helping managers to forecast and respond immediately and effectively. Developments of such systems are already taking place. For example, a mobile sensor to capture images, AI to detect and identify animals from the images, and transmission of information over a mobile network to warn of animal presence show great potential for mitigating human-elephant conflict in Thailand (Mongabay, 2020). In addition, a centralized mobile application that allows local community members to submit information on tiger presence and behavior could have great potential in reducing conflicts. Mobile applications would make it convenient to report, communicate, and track conflicts and compensation, such as the open-source technology Wild Seve used in India (Karanth & Vanamamalai, 2020). Other technologies such as non-imaging sensors (Kamminga et al., 2018) can also be used to notify of tiger intrusions. Such systems could be cheaper, cover large areas, and provide real-time warnings, giving locals a chance to prepare and respond. Non-lethal deterrents such as fox lights to deter leopards in India (Naha et al., 2020), pumas in Chile (Ohrens, Bonacic & Treves, 2019), ultrasonic repellents to deter cats in Australia (Crawford, Fontaine & Calver, 2018), and LED flashlights in Kenya to deter lions (Lesilau et al., 2018), may also be a promising approach to tiger conflict management. Currently, such technologies are underutilized in South Asia. This could be due to the high costs involved with implementing new infrastructure and training personnel, reluctance to adopt new technology or a perceived

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

Supporting information
Additional supporting information may be found online in the Supporting Information section at the end of the article.
Appendix S1. Data on tiger increase and conflict cases.