AI-Driven-IoT(AIIoT) Based Decision-Making- KSK Approach in Drones for Climate Change Study
Kutubuddin Sayyad Liyakat Kazi, Suhas B Khadake, Dipti A. Tamboli, Vijay A. Sawant, H. M. Mallad, Sushil Sathe
Abstract
The use of artificial intelligence-driven Internet of Things (IoT) in drones offers the potential to improve how we understand and address this worldwide problem in the context of climate change research. It enables the collection of data more accurately and efficiently, which can help with the process of making better-informed judgments. On the contrary, it is crucial to resolve any potential ethical issues and ensure that this innovation is used to improve society. In the future, drones that use AIIoT could be a significant factor in reducing the negative effects of climate change. Currently, the KSK approach is being used to support climate change research. A database is created, compared to previous datasets, and a decision is made based on the results. Here, we look into the environment's temperature and carbon dioxide concentration. Tests are conducted to determine the system's accuracy and make comparisons between the decisions. Here, a K-NN, ANN, and DT approach is suggested. These techniques are employed to compare accuracy. The KSK method has a temperature accuracy of 94.3% and a CO2 accuracy of 94.5%.