{"id":{"repo_id":"buffalo","oai_identifier":"oai:ubir.buffalo.edu:10477/78585"},"canonical_url":"https://search.dev.ndltd.org/etd/buffalo/oai:ubir.buffalo.edu:10477/78585","repository":{"repo_id":"buffalo","name":"Buffalo","base_url":"https://ubir.buffalo.edu/oai/request"},"display":{"title":"Using an Intelligent UAV Swarm in Natural Disaster Environments","abstract":"M.S.","abstract_html":"M.S.","abstract_has_math":false,"creators":["Asbach, Ronald"],"institution":"State University of New York at Buffalo","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Lewis, Kemper","Mechanical and Aerospace Engineering"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-10-26T02:56:02Z","date_published":"2018-10-26T02:56:02Z","updated_at":"2026-07-27T19:05:12Z","subjects":["mechanical engineering","artificial intelligence"],"languages":["eng"],"rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10477/78585","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Lewis, Kemper","Mechanical and Aerospace Engineering"]},{"key":"dc:creator","label":"Author","values":["Asbach, Ronald"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2018-10-26T02:56:02Z","2018","2018-08-09 10:00:35"]},{"key":"dc:publisher","label":"Institution","values":["State University of New York at Buffalo"]},{"key":"dc:type","label":"Dc Type","values":["Text","Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["mechanical engineering","artificial intelligence"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/10477/78585"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["M.S.","Due to their volatile behavior, natural disasters are challenging problems that often cannot be accurately predicted. An efficient method to gather updated information of the status of a disaster, such as the location of any trapped survivors, is extremely important to properly conduct rescue operations. To accomplish this, an algorithm is presented to control a swarm of UAVs and optimize the value of the information gathered by this swarm. With sensor technology embedded, this swarm collects information from the environment as it navigates with a decentralized control method. By using the swarm’s location history, areas of the environment with the highest probability of containing unidentified survivors can be prioritized, ensuring an efficient search. Measures are also developed to prevent redundant exploration, which would reduce the value of the information gathered. A case study of the Puerto Rico floods in 2017 is examined and simulated for validation. Through this approach, the value of the proposed swarm algorithm can be tested by tracking the number of survivors found as well as the rate at which they are discovered."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Using an Intelligent UAV Swarm in Natural Disaster Environments"]}]}],"canonical_facts":{"dc:contributor":["Lewis, Kemper","Mechanical and Aerospace Engineering"],"dc:creator":["Asbach, Ronald"],"dc:date":["2018-10-26T02:56:02Z","2018","2018-08-09 10:00:35"],"dc:description":["M.S.","Due to their volatile behavior, natural disasters are challenging problems that often cannot be accurately predicted. An efficient method to gather updated information of the status of a disaster, such as the location of any trapped survivors, is extremely important to properly conduct rescue operations. To accomplish this, an algorithm is presented to control a swarm of UAVs and optimize the value of the information gathered by this swarm. With sensor technology embedded, this swarm collects information from the environment as it navigates with a decentralized control method. By using the swarm’s location history, areas of the environment with the highest probability of containing unidentified survivors can be prioritized, ensuring an efficient search. Measures are also developed to prevent redundant exploration, which would reduce the value of the information gathered. A case study of the Puerto Rico floods in 2017 is examined and simulated for validation. Through this approach, the value of the proposed swarm algorithm can be tested by tracking the number of survivors found as well as the rate at which they are discovered."],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/10477/78585"],"dc:language":["eng"],"dc:publisher":["State University of New York at Buffalo"],"dc:rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"dc:subject":["mechanical engineering","artificial intelligence"],"dc:title":["Using an Intelligent UAV Swarm in Natural Disaster Environments"],"dc:type":["Text","Thesis"]},"updated_at":"2026-07-27T19:05:12Z"}