On safari with TensorFlow: Assisting tourism in rural Southern Africa using machine learning

Abstract

Tourism is a major contributor to employment in southern Africa and a major contributor to gross domestic products of many southern African countries. One of the major tourist attractions in many southern African countries is the wild animals. Major national parks such as Etosha in Namibia and Central Kalahari in Botswana often have rangers available to assist tourists on their game safaris by recognising animals and describing their habitats. Many of the smaller reserves, however, do not have the luxury of rangers available to tourists. At such smaller reserves, tourists are left on their own to recognise the various animals. This paper describes the use of Google’s TensorFlow to create an image recogniser trained for southern African mammals. The recogniser was embedded in an Android mobile app and could then assist tourists at smaller reserves.