LOCATING MISSING PERSONS USING ARTIFICIAL INTELLIGENCE
Main Article Content
Abstract
Every day more than five hundred missing person complaints are approximated to go unanswered in India. an organization called as find me group FMG that is currently active in the united states led by former field experts is committed to solve the problems that lead to such scenarios. they have introduced and made use of the missing person intelligence synthesis toolkit mist which adopts a driven-data approach to the given problem. using the same approach and slightly building upon the foundation provided by FMG we aim to tackle this problem by taking search locations on the basis of the data on hand ranks and orders the locations based on the likelihood as well as the probability allocated to the search areas based on the prior information and previous performances that are taken individually as well as a group. we compared and contrasted our approach with the current practices adopted by several organizations and entities and found that this method gives us a slight but significant advantage over many of such approaches. it is worth noteworthy that it could actually reduce the search area leading to a reduction of many square kilometres over several cases that were examined in the conducted experiments. missing individual incidents have been on a steady rise in India for the past many years. the major cause of many of these incidents never being solved the lack of timely reporting of such cases and the lack of transparency of facts and information. and because of this sadly many of those cases are never solved. the cases of human trafficking and homicides are other fields that can be tackled by this approach as many of their attributes match.
Â
Downloads
Article Details
COPYRIGHT
Submission of a manuscript implies: that the work described has not been published before, that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication, the authors agree to automatic transfer of the copyright to the publisher.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
- The journal allows the author(s) to retain publishing rights without restrictions.
- The journal allows the author(s) to hold the copyright without restrictions.
References
B. Akinkunmi and P. C. Bassey. A Logic of Spatial Qualification Using Qualitative Reasoning Approach. International Journal of Artificial Intelligence & Applications, 2017.
T. Bylander, D. Allemang, M. C. Tanner, and J. R. Josephson. The Computational Complexity of Abduction. Artificial Intelligence. 2016.
L. Console, L. Portinale, and D. T. Dupre. Focussing Abductive Diagnosis. AI Communication, 2016
L. Console, M. L. Sapino, and D. T. Dupre. The Role of Abduction in Database View Updating. J. Intel. Inf. Syst., 2017.
S. do Ago Pereira and L. N. de Barros. Planning with abduction: A logical framework to explore extensions to classical planning. In Brazilian Symposium on Artificial Intelligence, pages 62-72., 2018.