Revolutionizing UTI Treatment: Harnessing Ant Colony Optimization for Effective E. coli Combat in the Urinary Tract

This research presents a bio-inspired nanorobot swarming algorithm based on Ant Colony Optimization (ACO) for combating Escherichia coli ( E. coli ) in Urinary Tract Infections (UTIs). UTIs caused by E. coli are a major global health concern. An approach that mimics the collective behavior of ant colonies in foraging tasks, utilizing ACO principles to guide the navigation and targeting of nanobots within the urinary tract, was proposed. Using NetLogo, an agent-based modeling platform, simulation and evaluation of the nanorobot swarm's performance was carried out. The swarm consists of autonomous agents that mimic ant behavior, with E. coli bacteria as the target. The efficacy of the ACO-based algorithm in eradicating E. coli in UTIs was demonstrated through extensive experimentation. Experimental results show that the algorithm successfully guides nanobots to locate and neutralize E. coli bacteria, reducing infection levels. The investigation also investigated the impact of parameters like pheromone evaporation rates and agent communication strategies on swarm performance. This research contributes to nanorobot technology advancement and highlights the potential of bio-inspired algorithms for medical challenges. The proposed ACO-based algorithm offers a targeted and efficient approach to combat E. coli infections in UTIs. Insights gained from this study can guide further research and development of nanorobot-based therapies for urinary tract infections and other infectious diseases.