Internet of things (IoT) based shortest route between departments within a university by applying nature inspired computing (NIC) algorithm

Nature Inspired Computing Algorithms are the best solutions for solving complex problems around us. The objective of our paper use Ant Colony Optimization (ACO) to optimize the shortest route between various departments located in university campus. The Internet of Things (IoT) technologies by navig...

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Bibliographic Details
Main Authors: Phridviraj, M. S. B., Srinivas, C., Venkatramulu, S., Rao, V. Chandra Shekhar, Pratapagiri, Sreenivas, Mahender, K.
Format: Conference Proceeding
Language:English
Subjects:
Algorithms
Ant colony optimization
Apexes
Applications programs
Cell phones
College campuses
Colleges & universities
Graph theory
Internet of Things
Mobile computing
Shortest-path problems
Online Access:Get full text
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Summary:Nature Inspired Computing Algorithms are the best solutions for solving complex problems around us. The objective of our paper use Ant Colony Optimization (ACO) to optimize the shortest route between various departments located in university campus. The Internet of Things (IoT) technologies by navigation of mobile application to find shortest path located by online graphical form in a SR University campus. A graph is generated by MATLAB and the simulation results showing information of shortest route of source to destination & neighbour information. The working procedure of ACO is edge(departments) between vertices(paths) then maintain the pheromone level at that edge should be higher. As per pheromone level is high on that path, other ants also follow this path, or otherwise omitted the edge. The paper focus on Internet of Things (IoT) based ACO Optimized intelligent system for mobile phone application that students and visitors found nearest location within shortest time selective locations within SR University campus. For that save time and flexibility to find short route in a reasonable amount of time while using NIC based algorithm.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0086030