Global climate change and increased anthropogenic activities are responsible for outbreaks of invasive and endemic pests, diseases, and pathogens. Forest pests pose serious threats to the growth, productivity, and resilience of natural forests and green urban spaces globally. To cope with the hazardous impacts of trunk-boring pests on forest degradation, it is crucial to detect their infestations at early growth stages. However, the borer larvae’s hidden lifestyle and delayed apparent symptoms lead to widespread infestation, resulting in large-scale tree mortality. The development of smart systems is critical to protecting natural forests and forest plantations from the fatal impacts of boring pests. Applications of artificial intelligence (AI), Internet of Things (IoT), and remote sensing (RS) technologies are transforming traditional pest management strategies by developing more sustainable and robust solutions. The integration of these cutting-edge technologies is paving the way for early pest detection, identification, and outbreak prediction by implementing on-site decision support systems (DSS) and remote monitoring of agricultural fields and large-scale forests. Advanced IoT acoustic sensors can record vibrational signals of boring pest larvae activities inside the tree trunk to confirm pest infestations at early stages, assisting forest management stakeholders in taking preventive measures to suppress the pests’ outbreaks in a timely manner. Auditory signals recorded by piezoelectric sensors are affected by external environmental noise. To improve pest detection ability, different AI-based signal enhancement algorithms are deployed to suppress noisy signals and process enhanced signals. Enormously improved RS technologies can monitor dynamic structural changes in forests by capturing multispectral images through satellites and drones equipped with high-resolution cameras, and then the RS data are incorporated into advanced AI algorithms to analyze the pests and disease-induced stress in the forest ecosystem to develop smart forest protection systems. The integration of X-ray imaging and deep learning models is another achievement in the non-destructive management of trunk-boring pests.
Bibi et al. (Wed,) studied this question.