Despite the growing population of tigers in India, many problems including poaching and natural causes are making it difficult for these majestic animals to survive. Now, new technologies like artificial intelligence, geographic information system tools and movement detectors, are changing the way tiger reserves and conservation bodies are working across India.
“For an animal that requires no human intervention to thrive, yet needs human protection, technology may be the only path to conservation,” wrote Souma Das, managing director at Teradata India, for a national newspaper.
For example, earlier this year, the All-India Tiger Estimation, 2018 exercise explained how the current assessment for tiger conservation used Android-based application and desktop version of M-STrIPES (Monitoring System for Tigers-Intensive Protection and Ecological Status) for collecting, archiving and analysing data. The mobile phone-based application automatically records the track log of surveys and line transects, as well as authenticates the recorded data on signs and animal sightings with geo-tagged photographs.
A statement issued by the Press Information Bureau for the Ministry of Environment, Forest and Climate Change, stated that with increased camera trap density and the use of android technology, estimates arrived at are likely to be more robust — both in terms of accuracy and precision.
This becomes evident from the fact that compared to the exercise conducted in the year 2006, when 9, 700 cameras were put up, the 2018 Estimation will use nearly 15, 000 cameras.
The Tiger Estimation exercise is the world’s largest wildlife survey effort in terms of coverage, the intensity of sampling and quantum of camera trapping. An amount of ₹10.22 crore was to be invested by the Government in the fourth cycle of All India Tiger Estimation. Financial assistance to the tune of ₹7 crore was to be provided to the States through the ongoing Centrally Sponsored Scheme of Project Tiger.
In 2016, a newly-developed AI called PAWS (Protection Assistant for Wildlife Security) used machine learning to help rangers fight poachers in Africa.
