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Optimization and Implementation of Drone-Assisted Blood Bag Delivery Models and Algorithms

Optimization and Implementation of Drone-Assisted Blood Bag Delivery Models and Algorithms
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Author(s): Tejinder Singh Lakhwani (IIT Jodhpur, India), Yerasani Sinjana (IIT Jodhpur, India)and Anuj Pal Kapoor (IIT Jodhpur, India)
Copyright: 2025
Pages: 46
Source title: Environmental Monitoring Technologies for Improving Global Human Health
Source Author(s)/Editor(s): Olga Anatolievna Pasko (National Open Institute, St. Petersburg, Russia)and Nadezhda Anatolievna Lebedeva (International Personnel Academy, Germany)
DOI: 10.4018/979-8-3693-8532-6.ch014

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Abstract

The integrated use of drones, particularly in delivering blood bags in the healthcare sector, presents an innovative solution to challenges like congestion and geographical barriers in land transport. This chapter examines improvements and expanded applications of drone-assisted blood transportation, focusing on models, algorithms, and infrastructures. These include Mixed Integer Linear Programming (MILP), Dynamic Programming (DP), and heuristic control policies, all of which have proven to enhance the effectiveness and resilience of healthcare systems. These models help minimize costs, time, and resources, ensuring timely delivery of essential medical supplies. The chapter also delves into technological aspects such as battery life, load capacity, and communication connectivity, which are vital for drones to operate efficiently. Additionally, it highlights examples from Rwanda and Ghana, showing the viability of scaling drone delivery systems in different settings, while exploring current trends and future directions for integrating drones into healthcare supply chains.

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