Assessment of Radio-Frequency Radiation Levels from Cellular Base Transceiver Stations in Residential Areas and Their Potential Health Effects on Humans
- Authors
-
-
Adesoye S. ADEGOKE
Author
-
Lateef A. OTEGBEYE
Author
-
Olufemi S. SONEYE
Author
-
Oluwole O. GREEN
Author
-
Patrick O. OLABISI
Author
-
- Keywords:
- Base Transceiver Station (BTS), Electromagnetic Radiation, Power Density, Specific Absorption ratio (SAR).
- Abstract
-
The exponential growth in need for cellular mobile communication has resulted in a significant increase in the number of base transceiver stations across the country. These base transceiver stations are known to emit electromagnetic radiations and some are located very close to residential areas. This proximity to residential areas has prompted a heightened public and scientific concern over the potential health hazard of electromagnetic radiations from base stations on human body. This research work has carried out experimental investigations aimed at estimating levels of radiations from selected base stations and evaluate their potential health risk associated with the exposure. A handheld transmogmeter was used to measure power densities across selected base transmitter stations within some densely populated areas in Ikorodu area of Lagos State. Results of our investigation show an average measured values within the ranges of 0.0064w/m2 to 0.0187w/m2. This is considered extremely low when compared with exposure safety level as recommended by International Commission on Non Ionizing Radiation Protection. From our results, it can be inferred that no significant health hazard may arise as a result of radiation exposure on human body within the limit of our experimental data.
- References
- Downloads
- Published
- 26-06-2026
- Section
- Articles
- License
-
Copyright (c) 2026 FUDMA Journal of Engineering and Technology

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
Similar Articles
- Muhammad M. HAMIDU, Mathew KATAMBI, Omar FARUQ, Techno-Economic and Environmental Assessment of a Solar PV-Based Microgrid for Residential Electrification in Gwange I, Maiduguri Using HOMER Pro , FUDMA Journal of Engineering and Technology: Vol. 1 No. 2 (2025): December 2025
- Usman A. ABDURRAHMAN, Abdulkadir A. BICHI, Usman HARUNA, Akibu M. ABDULLAHI, A Hybrid Graph Neural Network Framework Integrating Handcrafted Features for Real-Time Iris Recognition in Motion , FUDMA Journal of Engineering and Technology: Vol. 2 No. 1 (2026): June 2026
- Afeez A. AWOLOKUN, Olusegun O. ALUKO, Temitope F. AWOLUSI, Mayowa A. OGIDI, Performance Evaluation of Pervious Concrete Containing Glass Cullet and Glass Powder for Sustainable Construction , FUDMA Journal of Engineering and Technology: Vol. 2 No. 1 (2026): June 2026
- Olusiji A. ADEYANJU, Joseph O. OLAIDE, Machine Learning Models for Predicting Flow Rate for Niger Delta Oil Wells , FUDMA Journal of Engineering and Technology: Vol. 2 No. 1 (2026): June 2026
- Sulaiman Y. ADAMU, Fadimatu N. DABAI, Abdulazeez Y. ATTA, Baba Y. JIBRIL, Preparation and Characterization of Enhanced Hierarchical Zn-Ni/HZSM-5 Catalysts for Potential use in Catalytic reactions to Upgrade Bio-Oil and Hydrogen from Biomass Pyrolysis , FUDMA Journal of Engineering and Technology: Vol. 1 No. 2 (2025): December 2025
- Nnamdi S. OKOMBA, Adedayo A. SOBOWALE, Adebimpe O. ESAN, Bolaji A. OMODUNBI, Taiwo A. AWOYEMI, Development of an Intelligent-Based Elevator System , FUDMA Journal of Engineering and Technology: Vol. 1 No. 2 (2025): December 2025
- Oluwayinka. G. AKINWAMIDE, Olugbenga O. AMU, Christopher FAPOHUNDA, Prediction of International Roughness Index of Flexible Pavement Using Machine Learning-Based Predictive Framework in Ekiti State , FUDMA Journal of Engineering and Technology: Vol. 2 No. 1 (2026): June 2026
- Dandison M. WALI, Beabu B. DUMKHANA, Raymond A. EKEMUBE, Silas O. NKAKINI, Smart Assessment of Tractor Noise Levels During Tillage Operation , FUDMA Journal of Engineering and Technology: Vol. 1 No. 2 (2025): December 2025
- Caleb A. ABORISADE, Jide E.T. AKINSOLA, Ifeoluwa M. OLANIYI, Fathia O. ONIPEDE, Emmanuel A. OLAJUBU, Ganiyu A. ADEROUNMU, Machine Learning-Based Polycystic Ovary Syndrome Generative Modelling via Ensemble Learning and Neural Networks for Infertility Prediction , FUDMA Journal of Engineering and Technology: Vol. 1 No. 1 (2025): July 2025
- Abubakar A. IBRAHIM, Fatimah Y. GARBA, Fatimah A. MUHAMMAD, Ismail B. ADEFESO, Bello A. ISAH, Jacob OLAYIWOLA, Industrial and Biomedical Applications Biobased Polymers of Polylactic Acid and Polyhydroxybutyrate: A Review , FUDMA Journal of Engineering and Technology: Vol. 1 No. 2 (2025): December 2025
You may also start an advanced similarity search for this article.
