Toronto Metropolitan University

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Toward the Automation of Search and Rescue Operations: An Algorithm for Finding Missing Lost Persons Living With Dementia Using Drones

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posted on 2023-06-05, 15:37 authored by Dalia Hanna

Unmanned Aerial Vehicles (UAV) are now used in many applications. The focus in this research work is on their use for public safety, specifically in Search and Rescue (SAR) operations involving Lost Persons Living With Dementia (LPLWD). When it comes to saving lives, there are many human factors associated with UAV operations that impact the performance of expert human SAR teams that could be improved through some form of automation. These include familiarity with the search location, and tasks associated with piloting and search/flight management during SAR operations. An LPLWD may not be interested in assisting in their own rescue as they may not know they are lost. As such, it has been observed that they tend to keep walking until they are faced with an obstacle that bars their continued progress. The approach presented in this research work focuses on developing a people-finding method to identify high-probability locations where an LPLWD might be found through informed, behavior-based analysis of the search location, and then developing an algorithm to fly a UAV to the vicinity of these high-probability locations. The algorithm was validated through field testing. The results from both the data collection process and the field tests indicated that there were efficiencies in using the drone, which enhanced the probability of finding the lost person alive. An informed process, involving automated approaches using R software to scrub and augment the data by adding any missing values in the dataset, helped to clarify the behaviour of the lost person and determine what significant variables enhanced their survivability. Linear regression was utilized to acquire the correlations between the numeric values in the database. Logistic regression and classification models were used to investigate 


The final goal of this work is to address the possibility of automating certain types of SAR. The outcome will also inform the design of use cases that could be used in various test environments.





  • Doctor of Philosophy


  • Computer Science

Granting Institution

Ryerson University

LAC Thesis Type

  • Dissertation

Thesis Advisor

Dr. Alex Ferworn



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