Welcome to the InfoSci Platform
Reference Hub3
Veco-Taxis as a Novel Engineered Algorithm for Odor Source Localization

Veco-Taxis as a Novel Engineered Algorithm for Odor Source Localization

Kumar Gaurav, Ajay Kumar, Ram Dayal
Copyright: © 2020 |Volume: 11 |Issue: 2 |Pages: 29
ISSN: 1941-6237|EISSN: 1941-6245|EISBN13: 9781799805724|DOI: 10.4018/IJACI.2020040101
Cite Article Cite Article

MLA

Gaurav, Kumar, et al. "Veco-Taxis as a Novel Engineered Algorithm for Odor Source Localization." IJACI vol.11, no.2 2020: pp.1-29. http://doi.org/10.4018/IJACI.2020040101

APA

Gaurav, K., Kumar, A., & Dayal, R. (2020). Veco-Taxis as a Novel Engineered Algorithm for Odor Source Localization. International Journal of Ambient Computing and Intelligence (IJACI), 11(2), 1-29. http://doi.org/10.4018/IJACI.2020040101

Chicago

Gaurav, Kumar, Ajay Kumar, and Ram Dayal. "Veco-Taxis as a Novel Engineered Algorithm for Odor Source Localization," International Journal of Ambient Computing and Intelligence (IJACI) 11, no.2: 1-29. http://doi.org/10.4018/IJACI.2020040101

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Algorithms with limited intelligence are unable to localize an odor source in an indoor environment with weak or no airflow. Stage wise solutions to odor source localization has been provided with a novel engineered algorithm called veco-taxis for plume traversal. It finds turn angles by calculating concentration gradients using vector algebra-based search algorithms. Levy walk is used in the plume finding phase. The concept of last chemical detection points (LCDPs) has been adopted for source declaration. The success rate of implemented algorithms is quantified using minimum and maximum move lengths—a key parameter—during source localization. A unified success and performance index (SPI) of the search algorithm is presented for the first time. SPI uncovers implicit parameters accountable for success in locating source and considers a qualitative performance. Higher SPIs are observed when the move length in plume finding is minimum and kept smaller than the plume traversal move length by some factor. It has been also demonstrated through simulations that veco-taxis is superior to the E. coli algorithm.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.