A Multi-Sensory Bioinformatics Framework for Ecological Modelling of Insect Behavior

Abstract

Insect behaviour plays a fundamental role in maintaining ecosystem stability, biodiversity, pollination, pest regulation, and agricultural productivity. However, conventional ecological studies often rely on isolated observations and single-source datasets, limiting the understanding of complex behavioural responses to dynamic environmental conditions. This review presents a comprehensive overview of a multi-sensory bioinformatics framework for ecological modelling of insect behaviour by integrating biological knowledge, bioinformatics, smart sensor networks, and artificial intelligence. The review examines the major sensory modalities governing insect behaviour, including visual, olfactory, acoustic, vibrational, thermal, and environmental sensing, and discusses how these signals influence navigation, communication, foraging, reproduction, and ecological adaptation. Recent advances in genomics, transcriptomics, multi-omics integration, and bioinformatics are explored to demonstrate their role in uncovering the molecular mechanisms underlying behavioural responses. Furthermore, the review highlights the contributions of Internet of Things (IoT)-enabled wireless sensor networks, computer vision, environmental monitoring systems, and unmanned sensing platforms in facilitating continuous, real-time ecological observations. The integration of machine learning, deep learning, explainable artificial intelligence, and multimodal data fusion enables accurate behavioural prediction, ecological forecasting, and intelligent decision support. Finally, current challenges, including heterogeneous data integration, interoperability, scalability, and model interpretability, are discussed together with emerging research directions such as digital twins, edge intelligence, and autonomous ecological monitoring. The proposed framework provides a holistic foundation for advancing ecological informatics and supporting sustainable agriculture, biodiversity conservation, and ecosystem management.