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Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Environmental Sources Policy & Risk Sign in to save

Chemical Detection Using Mobile Platforms and AI-Based Data Processing Technologies

Journal of Sensor and Actuator Networks 2025 6 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 53 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Daegwon Noh, Eunsoon Oh

Summary

This review examines the use of mobile platforms such as smartphones and drones equipped with chemical sensors for environmental monitoring, including air pollution and industrial waste detection. Researchers surveyed various sensor technologies and how machine learning is being applied to improve the accuracy of chemical detection from portable devices. While broadly focused on chemical sensing, the work is relevant to developing field-deployable monitoring tools for environmental contaminants including microplastic-associated pollutants.

The development of reliable gas sensors is very important in many fields such as safety, environment, and agriculture, and is especially essential for industrial waste and air pollution monitoring. As the performance of mobile platforms equipped with sensors such as smartphones and drones and the technologies supporting them (wireless communication, battery performance, data processing technology, etc.) are spreading and improving, a lot of efforts are being made to perform these tasks by using portable systems such as smartphones or installing them on unmanned wireless platforms such as drones. For example, research is continuously being conducted on chemical sensors for field monitoring using smartphones and rapid monitoring of air pollution using unmanned aerial vehicles (UAVs). In this paper, we review the measurement results of various chemical sensors available on mobile platforms including drones and smartphones, and the analysis of detection results using machine learning. This topic covers a wide range of specialized fields such as materials engineering, aerospace engineering, physics, chemistry, environmental engineering, electrical engineering, and machine learning, and it is difficult for experts in one field to grasp the entire content. Therefore, we have explained various concepts with relatively simple pictures so that experts in various fields can comprehensively understand the overall topics.

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