Title
Adaptive Sensing Scheme Using Naive Bayes Classification For Environment Monitoring With Drone
Abstract
Environmental sensors are important for collecting data to understand environmental changes and analyze environmental issues. In order to effectively monitor environmental changes, high-density sensor deployment and evenly distributed spatial distance between sensors become the requirements and desired properties for such applications. In many applications, sensors are deployed in locations that are difficult and dangerous to reach (e.g. mountaintop or skyscraper roof). To collect data from those sensors, unmanned aerial vehicles are used to act as data mules to overcome the problem of collecting data in challenging environments. In this article, we extend the adaptive return-to-home sensing algorithm with a parameter-tuning algorithm that combines naive Bayes classification and binary search to adapt adaptive return-to-home sensing parameters effectively on the fly. The proposed approach is able to (1) optimize number of sensing attempts, (2) reduce oscillation of the distance for consecutive attempts, and (3) reserve enough power for drone to return-to-home. Our results show that the naive Bayes classification-enhanced adaptive return-to-home sensing scheme is able to avoid oscillation in sensing and guarantees return-to-home feature while behaving more cost-effective in parameter tuning than the other machine learning-based approaches.
Year
DOI
Venue
2018
10.1177/1550147718756036
INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS
Keywords
Field
DocType
Adaptive sensing, naive Bayes classification, environment monitoring, drone coordination, sensor network
Software deployment,Naive Bayes classifier,Computer science,On the fly,Real-time computing,Drone,Binary search algorithm,Wireless sensor network,Adaptive sensing,Distributed computing
Journal
Volume
Issue
ISSN
14
1
1550-1477
Citations 
PageRank 
References 
0
0.34
4
Authors
3
Name
Order
Citations
PageRank
Yao Hua Ho18413.79
Yu-Te Huang2193.21
Hao-Hua Chu3116898.54