Biotica Research Today | Volume 8 Issue 4 | Pages: 55-58

Popular Article

OPEN ACCESS | Published on : 07-Apr-2026

Real-Time Monitoring: A New Era in Insect Population Surveillance

• Pavani P.S.
• Dept. of Entomology, College of Agriculture, University of Agricultural Sciences, Raichur, Karnataka (584 104), India

Suresha G.V.
• Dept. of Entomology, College of Agriculture, University of Agricultural Sciences, Raichur, Karnataka (584 104), India

Rekha R. Biradar
• Dept. of Entomology, College of Agriculture, University of Agricultural Sciences, Raichur, Karnataka (584 104), India

Shweta
• Dept. of Entomology, College of Agriculture, University of Agricultural Sciences, Raichur, Karnataka (584 104), India

Abstract

The reduction of biodiversity is a major threat to the world and the rate at which insects are substantially depleting is a great cause of concern also. It is estimated that insect species may lose about 65% of their populations in the next century and this can devastatingly affect the activities of an ecosystem including pollination, nutrient maintenance and food haunting. This crisis can be effectively addressed by real-time insect population monitoring that allows the constant evaluation of the number of species, their diversity and behaviour. Such methodology will help obtain crucial, time-sensitive information that is needed to guide informed conservation strategies and eventually, facilitate the sustainability and resilience of an ecosystem.

How to Cite

Pavani, P.S., Suresha, G.V., Rekha, R.B., Shweta., 2026. Real-time monitoring: A new era in insect population surveillance. Biotica Research Today 8(4), 55-58.

Keywords

Acoustic, Radar, Real time monitoring, Survey

References

• Bjerge, K., Nielsen, J.B., Sepstrup, M.V., Nielsen, H.F., Hoye, T.T., 2021. An automated light trap to monitor moths (Lepidoptera) using computer vision-based tracking and deep learning. Sensors 21(2), 343. DOI: https://doi.org/10.3390/s21020343.

  Doi, H., Katano, I., Sakata, Y., Souma, R., Kosuge, T., Nagano, M., Ikeda, K., Yano, K., Tojo, K., 2017. Detection of an endangered aquatic heteropteran using environmental DNA in a wetland ecosystem. Royal Society Open Science 4(1), 170568. DOI: https://doi.org/10.1098/rsos.170568.

  Jeliazkov, A., Bas, Y., Kerbiriou, C., Julien, J.F., Penone, C., Le Viol, I., 2016. Large-scale semi-automated acoustic monitoring allows to detect temporal decline of bush-crickets. Global Ecology and Conservation 6, 208-218. DOI: https://doi.org/10.1016/j.gecco.2016.02.008.

  Rydhmer, K., Bick, E., Still, L., Strand, A., Luciano, R., Helmreich, S., Beck, B.D., Gronne, C., Malmros, L., Poulsen, K., Elbaek, F., Brydegaard, M., Lemmich, J., Nikolajsen, T., 2022. Automating insect monitoring using unsupervised near-infrared sensors. Scientific Reports 12, 2603. DOI: https://doi.org/10.1038/s41598-022-06439-6.

  Stepanian, P.M., Entrekin, S.A., Wainwright, C.E., Mirkovic, D., Tank, J.L., Kelly, J.F., 2020. Declines in an abundant aquatic insect, the burrowing mayfly, across major North American waterways. The Proceedings of the National Academy of Sciences 117(6), 2987-2992. DOI: https://doi.org/10.1073/pnas.1913598117.