TECHNOLOGY AND METHODS OF COLLECTING INFORMATION FOR IDENTIFYING METAL OBJECTS IN TOPSOIL
Keywords:
metal detectors, pulse induction, Raspberry Pi, object identification, signal processing, topsoil, humanitarian deminingAbstract
Detection of metal objects lying at a shallow depth is a relevant task in archaeology, construction, ecology, mineral exploration and the field of mine safety. Research objective: To propose a method and technology for identifying a metal object with given parameters based on a comparison of modern methods and technologies for detecting metal objects. The paper analyzes existing detection methods such as electromagnetic induction metal detectors (EMI), ground penetrating radar (GPR), magnetometers, and non-linear junction detectors (NLJD). The choice of a pulse induction (PI) metal detector based on a Raspberry Pi single-board computer is justified as the optimal platform in terms of cost, performance, and versatility. The developed hardware part of the complex and an information system with a client-server architecture for data collection and primary processing are presented. A hypothetical stack of signal processing methods (band-pass filter, RPCA-GoDec, FFT, RBF-SVM) is proposed for identifying ferrous objects of a certain size.
References
Федоренко Г., Фесенко Г., Чарченко В. Аналіз методів і розроблення концепції гарантованого виявлення та розпізнавання вибухонебезпечних предметів // Innovative technologies and scientific solutions for industries. 2022. № 4(22). С. 24–35.
Вчені записки Таврійського національного університету імені В.І. Вернадського. Серія: Технічні науки. 2024. Том 35 (74), № 5, Частина 2. С. 153-158
Захожай О.І., Коррель В.В. Інформаційна технологія формування карти просторового розташування малорозмірних об’єктів для геоінформаційних систем // Наукові вісті Далівського університету. 2024. № 27. С. 2–4.
Lei Y., Jiang B., Su G. Comparative Study of GPR Acquisition Methods for Shallow-Buried Object Detection // Remote Sensing. 2025. Vol. 16, Iss. 21. Art. 3931. DOI: 10.3390/rs16213931.
Saleh M., Naim S. Development and Implementation of a Low-Cost PI Metal Detector Device // Bulletin of Electrical Engineering and Informatics. 2024. Vol. 13, № 2. P. 731–740.
Edemsky D. et al. A Comparative Study of Ground-Based and Drone-Based GPR // BIO Web of Conferences. 2025. Vol. 56. Art. 05004.
Al-Sabbagh S., Popov A. GPR Signal Processing for Landmine Detection: A Comparative Study // International Journal of Computer & Digital Systems. 2024. Vol. 13, № 4. P. 215–224.
Yilmaz E. Detection and Classification of Multiple Shallow-Buried Targets by GPR. MSc Thesis. Middle East Technical University, 2023.
Thomas R. et al. Machine learning classification of metallic objects using pulse-induction electromagnetic data // Measurement Science & Technology. 2024.
Jeong S. et al. Investigation of electromagnetic pulse scattering for metallic object classification // Journal of Electromagnetic Waves and Applications. 2024.
