Monitoring pest insect traps by means of low-power image sensor technologies

Monitoring pest insect populations is currently a key issue in agriculture and forestry protection. At the farm level, human operators typically must perform periodical surveys of the traps disseminated through the field. This is a labor-, time- and cost-consuming activity, in particular for large plantations or large forestry areas, so it would be of great advantage to have an affordable system capable of doing this task automatically in an accurate and a more efficient way. This paper proposes an autonomous monitoring system based on a low-cost image sensor that it is able to capture and send images of the trap contents to a remote control station with the periodicity demanded by the trapping application. Our autonomous monitoring system will be able to cover large areas with very low energy consumption. This issue would be the main key point in our study; since the operational live of the overall monitoring system should be extended to months of continuous operation without any kind of maintenance (i.e., battery replacement). The images delivered by image sensors would be time-stamped and processed in the control station to get the number of individuals found at each trap. All the information would be conveniently stored at the control station, and accessible via Internet by means of available network services at control station (WiFi, WiMax, 3G/4G, etc.). © 2012 by the authors; licensee MDPI, Basel, Switzerland.This work was partially funded by Ministry of Education and Science grants CTM2011-29691-C02-01, TIN2011-28435-C03-01 and TIN2011-27543-C03-03.López ., O.; Martinez Rach, MO.; Migallon ., H.; Pérez Malumbres, MJ.; Bonastre Pina, AM.; Serrano Martín, JJ. (2012). Monitoring pest insect traps by means of low-power image sensor technologies. Sensors. 12(11):15801-15819. doi:10.3390/s121115801S15801158191211Shelton, A. M., & Badenes-Perez, F. R. (2006). CONCEPTS AND APPLICATIONS OF TRAP CROPPING IN PEST MANAGEMENT. Annual Review of Entomology, 51(1), 285-308. doi:10.1146/annurev.ento.51.110104.150959Jiang, J.-A., Tseng, C.-L., Lu, F.-M., Yang, E.-C., Wu, Z.-S., Chen, C.-P., … Liao, C.-S. (2008). 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). Computers and Electronics in Agriculture, 62(2), 243-259. doi:10.1016/j.compag.2008.01.005http://www.memsic.comAl-Saqer. (2011). Red Palm Weevil (Rynchophorus Ferrugineous, Olivier) Recognition by Image Processing Techniques. American Journal of Agricultural and Biological Sciences, 6(3), 365-376. doi:10.3844/ajabssp.2011.365.376http://www.ti.com/lit/ds/symlink/cc1110f32.pdfhttp://www.comedia.com.hkOliver, J., & Perez Malumbres, M. (2008). On the Design of Fast Wavelet Transform Algorithms With Low Memory Requirements. IEEE Transactions on Circuits and Systems for Video Technology, 18(2), 237-248. doi:10.1109/tcsvt.2007.91396