{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T08:28:25Z","timestamp":1782894505922,"version":"3.54.5"},"reference-count":49,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2017,8,22]],"date-time":"2017-08-22T00:00:00Z","timestamp":1503360000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000780","name":"European Union","doi-asserted-by":"publisher","award":["605073 ENTOMATIC"],"award-info":[{"award-number":["605073 ENTOMATIC"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotics"],"abstract":"<jats:p>\u03a4he concept of remote insect surveillance at large spatial scales for many serious insect pests of agricultural and medical importance has been introduced in a series of our papers. We augment typical, low-cost plastic traps for many insect pests with the necessary optoelectronic sensors to guard the entrance of the trap to detect, time-stamp, GPS tag, and\u2014in relevant cases\u2014identify the species of the incoming insect from their wingbeat. For every important crop pest, there are monitoring protocols to be followed to decide when to initiate a treatment procedure before a serious infestation occurs. Monitoring protocols are mainly based on specifically designed insect traps. Traditional insect monitoring suffers in that the scope of such monitoring: is curtailed by its cost, requires intensive labor, is time consuming, and an expert is often needed for sufficient accuracy which can sometimes raise safety issues for humans. These disadvantages reduce the extent to which manual insect monitoring is applied and therefore its accuracy, which finally results in significant crop loss due to damage caused by pests. With the term \u2018surveillance\u2019 we intend to push the monitoring idea to unprecedented levels of information extraction regarding the presence, time-stamping detection events, species identification, and population density of targeted insect pests. Insect counts, as well as environmental parameters that correlate with insects\u2019 population development, are wirelessly transmitted to the central monitoring agency in real time and are visualized and streamed to statistical methods to assist enforcement of security control to insect pests. In this work, we emphasize how the traps can be self-organized in networks that collectively report data at local, regional, country, continental, and global scales using the emerging technology of the Internet of Things (IoT). This research is necessarily interdisciplinary and falls at the intersection of entomology, optoelectronic engineering, data-science, and crop science and encompasses the design and implementation of low-cost, low-power technology to help reduce the extent of quantitative and qualitative crop losses by many of the most significant agricultural pests. We argue that smart traps communicating through IoT to report in real-time the level of the pest population from the field straight to a human controlled agency can, in the very near future, have a profound impact on the decision-making process in crop protection and will be disruptive of existing manual practices. In the present study, three cases are investigated: monitoring Rhynchophorus ferrugineus (Olivier) (Coleoptera: Curculionidae) using (a) Picusan and (b) Lindgren trap; and (c) monitoring various stored grain beetle pests using the stored-grain pitfall trap. Our approach is very accurate, reaching 98\u201399% accuracy on automatic counts compared with real detected numbers of insects in each type of trap.<\/jats:p>","DOI":"10.3390\/robotics6030019","type":"journal-article","created":{"date-parts":[[2017,8,22]],"date-time":"2017-08-22T11:08:25Z","timestamp":1503400105000},"page":"19","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":63,"title":["Automated Remote Insect Surveillance at a Global Scale and the Internet of Things"],"prefix":"10.3390","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7111-3331","authenticated-orcid":false,"given":"Ilyas","family":"Potamitis","sequence":"first","affiliation":[{"name":"Department of Music Technology & Acoustics, Technological Educational Institute of Crete, E. Daskalaki Perivolia, 74100 Rethymno Crete, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2055-0950","authenticated-orcid":false,"given":"Panagiotis","family":"Eliopoulos","sequence":"additional","affiliation":[{"name":"Department of Agricultural Technologists, Technological Educational Institute of Thessaly, 41110 Larissa, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Iraklis","family":"Rigakis","sequence":"additional","affiliation":[{"name":"Department of Electronics, Technological Educational Institute of Crete, Romanou 3\u2014Chalepa, 73133 Chania, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2017,8,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1017\/S0021859605005708","article-title":"Crop losses to pests","volume":"144","author":"Oerke","year":"2006","journal-title":"J. Agric. Sci."},{"key":"ref_2","unstructured":"Oerke, E.C., Dehne, H.W., Sch\u00f6nbeck, F., and Weber, A. (2012). Crop Production and Crop Protection: Estimated Losses in Major Food and Cash Crops, Elsevier."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1525\/bio.2009.59.5.6","article-title":"New eyes on the world: Advanced sensors for ecology","volume":"59","author":"Porter","year":"2009","journal-title":"BioScience"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Mukhopadhyay, S.C., and Jayasundera, K.P. (2013). Ecological Monitoring Using Wireless Sensor Networks\u2014Overview, Challenges, and Opportunities. Smart Sensors, Measurement and Instrumentation, Springer. Book Section in Advancement in Sensing Technology, V. 1.","DOI":"10.1007\/978-3-642-32180-1_1"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"e103","DOI":"10.7717\/peerj.103","article-title":"Real-time bioacoustics monitoring and automated species identification","volume":"1","author":"Aide","year":"2013","journal-title":"PeerJ"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1590\/S0001-37652004000200037","article-title":"Automated bioacoustic identification of species","volume":"76","author":"Chesmore","year":"2004","journal-title":"An. Acad. Bras. Ci\u00eanc."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Potamitis, I. (2014). Automatic Classification of a Taxon-Rich Community Recorded in the Wild. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0096936"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1064","DOI":"10.1111\/j.1365-2664.2012.02182.x","article-title":"A continental-scale tool for acoustic identification of European bats","volume":"49","author":"Walters","year":"2012","journal-title":"J. Appl. Ecol."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Potamitis, I., Rigakis, I., and Tatlas, N.-A. (2017). Automated Surveillance of Fruit Flies. Sensors, 17.","DOI":"10.3390\/s17010110"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1681","DOI":"10.1603\/029.102.0436","article-title":"On Automatic Bioacoustic Detection of Pests: The Cases of Rhynchophorus ferrugineus and Sitophilus oryzae","volume":"102","author":"Potamitis","year":"2009","journal-title":"J. Econ. Entomol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3518","DOI":"10.1121\/1.429434","article-title":"Recognizing transient low-frequency whale sounds by spectrogram correlation","volume":"107","author":"Mellinger","year":"2000","journal-title":"J. Acoust. Soc. Am."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Ospina, O.E., Villanueva-Rivera, L.J., Corrada-Bravo, C.J., and Mitchell, A.T. (2013). Variable response of anuran calling activity to daily precipitation and temperature: Implications for climate change. Ecosphere.","DOI":"10.1890\/ES12-00258.1"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1007\/s10905-014-9454-4","article-title":"Flying insect classification with inexpensive sensors","volume":"27","author":"Chen","year":"2014","journal-title":"J. Insect Behav."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2808","DOI":"10.1093\/jee\/tov231","article-title":"Detection of Adult Beetles Inside the Stored Wheat Mass Based on Their Acoustic Emissions","volume":"108","author":"Eliopoulos","year":"2015","journal-title":"J. Econ. Entomol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.cropro.2016.04.001","article-title":"Estimation of population density of stored grain pests via bioacoustic detection","volume":"85","author":"Eliopoulos","year":"2016","journal-title":"Crop Prot."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1019","DOI":"10.1653\/024.098.0402","article-title":"Diel flight activity patterns of the red palm weevil (Coleoptera: Curculionidae) as monitored by smart traps","volume":"98","author":"Aldryhim","year":"2015","journal-title":"Fla. Entomol."},{"key":"ref_17","first-page":"95","article-title":"Daily activity and non-random occurrence of captures in the Asian palm weevils","volume":"26","author":"Fanini","year":"2014","journal-title":"Ethol. Ecol. Evolut."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1079\/BER200189","article-title":"A novel mechanism for time-sorting insect catches, and its use to derive the diel flight periodicity of brassica pod midge Dasineura brassicae (Diptera: Cecidomyiidae)","volume":"91","author":"Murchie","year":"2001","journal-title":"Bull. Entomol. Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"883","DOI":"10.1093\/jee\/66.4.883","article-title":"Codling moth: Influence of temperature and daylight intensity on periodicity of daily flight in the field","volume":"66","author":"Batiste","year":"1973","journal-title":"J. Econ. Entomol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1093\/ee\/14.3.199","article-title":"Portable electronic detector system used with inverted-cone sex pheromone traps to determine periodicity and moth captures","volume":"14","author":"Hendricks","year":"1985","journal-title":"Environ. Entomol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1303\/jjaez.38.197","article-title":"Automatic record using camera of diel periodicity of pheromone trap catches","volume":"38","author":"Kondo","year":"1994","journal-title":"Jpn. J. Appl. Entomol. Zool."},{"key":"ref_22","unstructured":"Engelmann, F. (1970). The Physiology of Insect Reproduction, Pergamon Press."},{"key":"ref_23","unstructured":"Saunders, D.S. (2002). Insect Clocks, Elsevier."},{"key":"ref_24","first-page":"39","article-title":"Electronic system for detecting trapped boll weevils in the field and transferring incident information to a computer","volume":"15","author":"Hendricks","year":"1990","journal-title":"Southwest. Entomol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.compag.2008.01.005","article-title":"A GSM-based remote wireless automatic monitoring system for field information: A case study for ecological monitoring of the oriental fruit fly, Bactrocera dorsalis (Hendel)","volume":"62","author":"Jiang","year":"2008","journal-title":"Comput. Electron. Agric."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"666","DOI":"10.1016\/j.agsy.2011.06.008","article-title":"Using automated monitoring systems to uncover pest population dynamics in agricultural fields","volume":"104","author":"Okuyama","year":"2011","journal-title":"Agric. Syst."},{"key":"ref_27","first-page":"135","article-title":"A review of the issues and management of the red palm weevil Rhynchophorus ferrugineus (Coleoptera: Rhynchophoridae) in coconut and date palm during the last one hundred years","volume":"26","author":"Faleiro","year":"2006","journal-title":"Int. J. Trop. Insect Sci."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1739","DOI":"10.1603\/EC13105","article-title":"Advances in the use of trapping systems for Rhynchophorus ferrugineus (Coleoptera: Curculionidae): Traps and attractants","volume":"106","author":"Vacas","year":"2013","journal-title":"J. Econ. Entomol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1111\/j.1570-7458.2008.00703.x","article-title":"Aggregation pheromone of the agave weevil, Scyphophorus acupunctatus","volume":"127","author":"Rojas","year":"2008","journal-title":"Entomol. Exp. Appl."},{"key":"ref_30","unstructured":"Aguilar, J.F.S., Hern\u00e1ndez, H.G., V\u00e1zquez, J.L.L., Mart\u00ednez, A.E., Mendoza, F.J.F., and Garza, \u00c1.M. (2001). Scyphophorus Acupunctatus Gyllenhal, Plaga del Agave Tequilero en Jalisco, M\u00e9xico, Colegio de Postgraduados."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1381","DOI":"10.1093\/jee\/84.4.1381","article-title":"Pitfall traps and grain samples as indicators of insects in farm-stored wheat","volume":"84","author":"Reed","year":"1991","journal-title":"J. Econ. Entomol."},{"key":"ref_32","first-page":"243","article-title":"21 Trapping and Interpreting Captures of Stored Grain Insects","volume":"21","author":"Toews","year":"2012","journal-title":"Stored Prod. Prot."},{"key":"ref_33","first-page":"506","article-title":"The development and use of pitfall and probe traps for capturing insects in stored grain","volume":"63","author":"White","year":"1990","journal-title":"J. Kansas Entomol. Soc."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.foodcont.2005.09.008","article-title":"Detection techniques for stored-product insects in grain","volume":"18","author":"Neethirajan","year":"2007","journal-title":"Food Control"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"45","DOI":"10.17221\/30\/2015-PPS","article-title":"Trapping of internal and external feeding stored grain beetle pests with two types of pitfall traps: A two-year field study","volume":"52","author":"Aulicky","year":"2016","journal-title":"Plant Prot. Sci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"299","DOI":"10.4039\/Ent115299-3","article-title":"A multiple funnel trap for scolytid beetles (Coleoptera)","volume":"115","author":"Lindgren","year":"1983","journal-title":"Can. Entomol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1139\/x05-241","article-title":"Mountain pine beetle population sampling: Inferences from Lindgren pheromone traps and tree emergence cages","volume":"36","author":"Bentz","year":"2006","journal-title":"Can. J. For. Res."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/S1881-8366(11)80016-9","article-title":"A GSM-based field monitoring system for Spodoptera litura (Fabricius)","volume":"4","author":"Shieh","year":"2011","journal-title":"Eng. Agric. Environ. Food"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.compag.2012.06.008","article-title":"Development of an autonomous early warning system for Bactrocera dorsalis (Hendel) outbreaks in remote fruit orchards","volume":"88","author":"Liao","year":"2012","journal-title":"Comput. Electron. Agric."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1016\/j.compag.2016.03.001","article-title":"A multi-target trapping and tracking algorithm for Bactrocera Dorsalis based on cost model","volume":"123","author":"Deqin","year":"2016","journal-title":"Comput. Electron. Agric."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"027001-1","DOI":"10.1117\/1.OE.51.2.027001","article-title":"In situ detection of small-size insect pests sampled on traps using multifractal analysis","volume":"51","author":"Xia","year":"2012","journal-title":"Opt. Eng."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.compag.2007.11.009","article-title":"A cognitive vision approach to early pest detection in greenhouse crops","volume":"62","author":"Boissard","year":"2008","journal-title":"Comput. Electron. Agric."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.compag.2016.02.003","article-title":"Automatic moth detection from trap images for pest management","volume":"123","author":"Ding","year":"2016","journal-title":"Comput. Electron. Agric."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"15801","DOI":"10.3390\/s121115801","article-title":"Monitoring pest insect traps by means of low-power image sensor technologies","volume":"12","author":"Rach","year":"2012","journal-title":"Sensors"},{"key":"ref_45","first-page":"247","article-title":"Automatic trap for moth detection in integrated pest management","volume":"64","author":"Guarnieri","year":"2011","journal-title":"Bull. Insectol."},{"key":"ref_46","unstructured":"Douglas, E.N. (2016, January 11\u201315). The Premonition Trap: First Field Trials of a Robotic Smart Trap for Mosquitoes with Species Recognition. Proceedings of the 47th Annual Conference of Society for Vector Ecology, Anchorage, Alaska."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Ma, J., Zhou, X., Li, S., and Li, Z. (2011, January 19\u201322). Connecting Agriculture to the Internet of Things through Sensor Networks. Proceedings of the 2011 International Conference on Internet of Things and 4th International Conference on Cyber, Physical and Social Computing, Dalian, China.","DOI":"10.1109\/iThings\/CPSCom.2011.32"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Shi, Y., Wang, Z., Wang, X., and Zhang, S. (2015, January 30\u201331). Internet of Things Application to Monitoring Plant Disease and Insect Pests. Proceedings of the China International Conference on Applied Science and Engineering Innovation (ASEI 2015), Xi\u2019an, China.","DOI":"10.2991\/asei-15.2015.7"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Shahzadi, R. (2016). Internet of Things based Expert System for Smart Agriculture, (IJACSA). Int. J. Adv. Comput. Sci. Appl., 7.","DOI":"10.14569\/IJACSA.2016.070947"}],"container-title":["Robotics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2218-6581\/6\/3\/19\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:42:58Z","timestamp":1760208178000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2218-6581\/6\/3\/19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,8,22]]},"references-count":49,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2017,9]]}},"alternative-id":["robotics6030019"],"URL":"https:\/\/doi.org\/10.3390\/robotics6030019","relation":{"has-preprint":[{"id-type":"doi","id":"10.20944\/preprints201705.0195.v1","asserted-by":"object"}]},"ISSN":["2218-6581"],"issn-type":[{"value":"2218-6581","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,8,22]]}}}