{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T05:21:38Z","timestamp":1779254498184,"version":"3.51.4"},"reference-count":22,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2020,11,11]],"date-time":"2020-11-11T00:00:00Z","timestamp":1605052800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotics"],"abstract":"<jats:p>Human ecology has played an essential role in the spread of mosquito-borne diseases. With standing water as a significant factor contributing to mosquito breeding, artificial containers disposed of as trash\u2014which are capable of holding standing water\u2014provide suitable environments for mosquito larvae to develop. The development of these larvae further contributes to the possibility for local transmission of mosquito-borne diseases in urban areas such as Zika virus. One potential solution to address this issue involves leveraging unmanned aerial vehicles that are already systematically becoming more utilized in the field of geospatial technology. With higher pixel resolution in comparison to satellite imagery, as well as having the ability to update spatial data more frequently, we are interested in investigating the feasibility of unmanned aerial vehicles as a potential technology for efficiently mapping potential breeding grounds. Therefore, we conducted a comparative study that evaluated the performance of an unmanned aerial vehicle for identifying artificial containers to that of conventionally utilized GPS receivers. The study was designed to better inform researchers on the current viability of such devices for locating a potential factor (i.e., small form factor artificial containers that can host mosquito breeding grounds) in the local transmission of mosquito-borne diseases. By assessing the performance of an unmanned aerial vehicle against ground-truth global position system technology, we can determine the effectiveness of unmanned aerial vehicles on this problem through our selected metrics of: timeliness, sensitivity, and specificity. For the study, we investigated these effectiveness metrics between the two technologies of interest in surveying a study area: unmanned aerial vehicles (i.e., DJI Phantom 3 Standard) and global position system-based receivers (i.e., Garmin GPSMAP 76Cx and the Garmin GPSMAP 78). We first conducted a design study with nine external participants, who collected 678 waypoint data and 214 aerial images from commercial GPS receivers and UAV, respectively. The participants then processed these data with professional mapping software for visually identifying and spatially marking artificial containers between the aerial imagery and the ground truth GPS data, respectively. From applying statistical methods (i.e., two-tailed, paired t-test) on the participants\u2019 data for comparing how the two technologies performed against each other, our data analysis revealed that the GPS method performed better than the UAV method for the study task of identifying the target small form factor artificial containers.<\/jats:p>","DOI":"10.3390\/robotics9040091","type":"journal-article","created":{"date-parts":[[2020,11,11]],"date-time":"2020-11-11T19:08:28Z","timestamp":1605121708000},"page":"91","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Identifying Potential Mosquito Breeding Grounds: Assessing the Efficiency of UAV Technology in Public Health"],"prefix":"10.3390","volume":"9","author":[{"given":"Jared","family":"Schenkel","sequence":"first","affiliation":[{"name":"Department of Geography, Rutgers University, New Brunswick, NJ 08901, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8950-0914","authenticated-orcid":false,"given":"Paul","family":"Taele","sequence":"additional","affiliation":[{"name":"Department of Computer Science &amp; Engineering, Texas A&amp;M University, College Station, TX 77843, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9304-7139","authenticated-orcid":false,"given":"Daniel","family":"Goldberg","sequence":"additional","affiliation":[{"name":"Department of Geography, Texas A&amp;M University, College Station, TX 77843, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3060-0894","authenticated-orcid":false,"given":"Jennifer","family":"Horney","sequence":"additional","affiliation":[{"name":"Program in Epidemiology, University of Delaware, Newark, DE 19713, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7272-0507","authenticated-orcid":false,"given":"Tracy","family":"Hammond","sequence":"additional","affiliation":[{"name":"Department of Computer Science &amp; Engineering, Texas A&amp;M University, College Station, TX 77843, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"482","DOI":"10.1603\/ME11227","article-title":"Constitutive differences between natural and artificial container mosquito habitats: Vector communities, resources, microorganisms, and habitat parameters","volume":"49","author":"Yee","year":"2012","journal-title":"J. Med. Entomol."},{"key":"ref_2","first-page":"187","article-title":"Container survey of mosquito breeding sites in a university campus in Kuala Lumpur, Malaysia","volume":"33","author":"Dhang","year":"2009","journal-title":"Dengue Bull."},{"key":"ref_3","unstructured":"Centers for Disease Control and Prevention (2020, July 10). Chikungunya Virus, Available online: http:\/\/www.cdc.gov\/chikungunya\/."},{"key":"ref_4","unstructured":"Centers for Disease Control and Prevention (2020, July 10). Dengue, Available online: http:\/\/www.cdc.gov\/dengue\/."},{"key":"ref_5","unstructured":"Centers for Disease Control and Prevention (2020, July 10). Zika Virus, Available online: http:\/\/www.cdc.gov\/zika\/vector\/range.html."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"514","DOI":"10.1016\/j.pt.2014.09.001","article-title":"Mapping Infectious Disease Landscapes: Unmanned Aerial Vehicles and Epidemiology","volume":"30","author":"Fornace","year":"2014","journal-title":"Trends Parasitol."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Arag\u00e3o, F., Zola, F., Marinho, L., de Genaro Chiroli, D., Junior, A., and Colmenero, J. (2020). Choice of unmanned aerial vehicles for identification of mosquito breeding sites. Geospat. Health, 15.","DOI":"10.4081\/gh.2020.810"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Suduwella, C., Amarasinghe, A., Niroshan, L., Elvitigala, C., De Zoysa, K., and Keppetiyagama, C. (2017, January 23). Identifying mosquito breeding sites via drone images. Proceedings of the 3rd Workshop on Micro Aerial Vehicle Networks, Systems, and Applications, Niagara Falls, NY, USA.","DOI":"10.1145\/3086439.3086442"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Dias, T., Alves, V., Alves, H., Pinheiro, L., Pontes, R., Araujo, G., Lima, A., and Prego, T. (2018, January 6\u201310). Autonomous Detection of Mosquito-Breeding Habitats Using an Unmanned Aerial Vehicle. Proceedings of the 2018 Latin American Robotic Symposium, 2018 Brazilian Symposium on Robotics (SBR) and 2018 Workshop on Robotics in Education (WRE), Joao Pessoa, Brazil.","DOI":"10.1109\/LARS\/SBR\/WRE.2018.00070"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2971","DOI":"10.3390\/rs70302971","article-title":"Intercomparison of UAV, Aircraft and Satellite Remote Sensing Platforms for Precision Viticulture","volume":"7","author":"Matese","year":"2015","journal-title":"Remote Sens."},{"key":"ref_11","first-page":"147","article-title":"Applying Chatbots to the Internet of Things: Opportunities and Architectural Elements","volume":"7","author":"Kar","year":"2016","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"key":"ref_12","unstructured":"Persson, C.G. (1995). Terrestrial Methods in Surveying, Mapping, and Establishment of Geographic Data Bases, National Land Survey. Technical Report Working Paper no. S-801."},{"key":"ref_13","first-page":"46","article-title":"Handheld GPS receiver accuracy","volume":"Volume 14","author":"Tiberius","year":"2003","journal-title":"GPS World"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2981\/wlb.00653","article-title":"Low-cost DIY GPS trackers improve upland game bird monitoring","volume":"2","author":"Kauth","year":"2020","journal-title":"Wildl. Biol."},{"key":"ref_15","first-page":"32","article-title":"Intelligent design and algorithms to control a stereoscopic camera on a robotic workspace","volume":"167","author":"Papoutsidakis","year":"2017","journal-title":"Int. J. Comput. Appl."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1111\/j.1467-9671.2012.01361.x","article-title":"Low Altitude Aerial Photography Applications for Digital Surface Models Creation in Archaeology","volume":"17","year":"2013","journal-title":"Trans. GIS"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Gilbertson, D.D., Kent, M., and Pyatt, F.B. (1985). Mapping and Aerial Photography. Practical Ecology for Geography and Biology, Springer. Chapter Aerial Photography and Satellite Imagery.","DOI":"10.1007\/978-1-4684-1415-8_10"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"567","DOI":"10.1111\/avsc.12072","article-title":"Unmanned aircraft systems help to map aquatic vegetation","volume":"17","author":"Husson","year":"2014","journal-title":"Appl. Veg. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"27","DOI":"10.5194\/isprsarchives-XL-1-W2-27-2013","article-title":"Accuracy of UAV photogrammetry compared with network RTK GPS","volume":"XL-1\/W2","author":"Barry","year":"2013","journal-title":"Int. Arch. Photogramm. Remote Sens."},{"key":"ref_20","unstructured":"Lozano-Fuentes, S., Ghosh, S., Bieman, J.M., Sadhu, D., Eisen, L., Hernandez-Garcia, E., Garcia-Rejon, J., Wedyan, F., and Tep-Chel, D. (2012, January 1\u20133). Using Cell Phones for Mosquito Vector Surveillance and Control. Proceedings of the 24th International Conference on Software Engineering and Knowledge Engineering, Redwood City, CA, USA."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"228","DOI":"10.2987\/19-6835.1","article-title":"Assessing Mosquito Breeding Sites and Abundance Using An Unmanned Aircraft","volume":"35","author":"Barretto","year":"2019","journal-title":"J. Am. Mosq. Control Assoc."},{"key":"ref_22","unstructured":"Case, E.H. (2017). MosquitoNet: Investigating the Use of Unmanned Aerial Vehicles and Neural Networks in Integrated Mosquito Management. [Master\u2019s Thesis, Cornell University]."}],"container-title":["Robotics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2218-6581\/9\/4\/91\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:32:12Z","timestamp":1760178732000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2218-6581\/9\/4\/91"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,11]]},"references-count":22,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2020,12]]}},"alternative-id":["robotics9040091"],"URL":"https:\/\/doi.org\/10.3390\/robotics9040091","relation":{},"ISSN":["2218-6581"],"issn-type":[{"value":"2218-6581","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,11]]}}}