Abstract
Climate change has become an accelerating problem in recent years due to pollutants like greenhouse gases, with carbon dioxide being the most prominent. Similarly in time, works on the application and development of swarm intelligence using drones, along with the use of drones to monitor air pollution/ source discovery, have been carried out in isolation to date. This paper presents an investigation to discover multiple pollution sources using a variety of existing swarm intelligence algorithms, through simulated drones. This paper also presents a bespoke Drone Hill Climber (DHC) algorithm that introduces the novel of multiple drones each flying on their own set paths, with the aim of finding multiple pollution peaks at efficient speeds.
| Original language | English |
|---|---|
| Title of host publication | 2024 IEEE 22nd Jubilee International Symposium on Intelligent Systems and Informatics (SISY) |
| Publisher | IEEE |
| Pages | 399-404 |
| DOIs | |
| Publication status | Published - 19 Sept 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 13 Climate Action
Keywords
- Air pollution monitoring
- Artificial bee colony
- Climate change
- Drone
- Firefly algorithm
- Particle swarm optimisation
- Simulations
- Swarm intelligence
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