Journal of Science, Technology and Environment Informatics
Volume 14 - Issue 01 | Year of Publication: 2025
Article type: Research Article | No. 88, 2025 | Country: Bangladesh | pp. 880-896 | Open Access
Title: Radiation distribution and associated hazard risks due to naturally occurring radioactive minerals at workplace
Authors: Saha Tumpa, Rajib Mohammad, Debnath Premanondo and Rasul Md. Golam
DOI: http://dx.doi.org/10.18801/jstei.140125.88
Title: Radiation distribution and associated hazard risks due to naturally occurring radioactive minerals at workplace
Authors: Saha Tumpa, Rajib Mohammad, Debnath Premanondo and Rasul Md. Golam
DOI: http://dx.doi.org/10.18801/jstei.140125.88
Radiation distribution and associated hazard risks due to naturally occurring radioactive minerals at workplace
Abstract
The study investigates radioactivity concentration and its associated health hazard indices as a part of workplace radiation monitoring. Institute of Nuclear Minerals (INM) deals with naturally occurring radioactive minerals (NORMs) and uses nuclear technology for the exploration of mineral resources for which elevated radioactivity is found at the workplace. A total of 34 measurements were conducted to identify those anomalous radioactive zones in and around INM. The measured radioactivity concentration of 238U, 232Th, and 40K were in the range of 52.49-170.31 bq/kg, 36.05-72.88 bq/kg and 291-697.99 bq/kg, respectively and corresponding dose rates were 0.09-0.21 µSv/h. The radioactivity levels found that its average concentration in the investigated area surpassed the world average values for each of uranium, thorium, and potassium. Concerning radiological risk measurements, radium equivalent activity index (Raeq), external hazard index (Hex), and internal hazard index (Hin) were generally below the world accepted limits, except for one case. Nevertheless, the recorded absorbed dose rate (DR) and the average annual effective dose equivalent (AEDE) from all devices exceeded world standards. The radioactivity distribution showed higher dose rates resulting from higher radionuclide presence in various types of samples collected from different geologically potential areas. Increased dose rates evident at the northern side of the building is probably from the combined effect of various radioactive samples, uncovered old mosaic floor and radon in air concentration in old storage.
Key Words: Spatial distribution, Occupational worker, Radiation exposure, NORMs, Annual effective dose, Gamma survey meters, ALARA
Abstract
The study investigates radioactivity concentration and its associated health hazard indices as a part of workplace radiation monitoring. Institute of Nuclear Minerals (INM) deals with naturally occurring radioactive minerals (NORMs) and uses nuclear technology for the exploration of mineral resources for which elevated radioactivity is found at the workplace. A total of 34 measurements were conducted to identify those anomalous radioactive zones in and around INM. The measured radioactivity concentration of 238U, 232Th, and 40K were in the range of 52.49-170.31 bq/kg, 36.05-72.88 bq/kg and 291-697.99 bq/kg, respectively and corresponding dose rates were 0.09-0.21 µSv/h. The radioactivity levels found that its average concentration in the investigated area surpassed the world average values for each of uranium, thorium, and potassium. Concerning radiological risk measurements, radium equivalent activity index (Raeq), external hazard index (Hex), and internal hazard index (Hin) were generally below the world accepted limits, except for one case. Nevertheless, the recorded absorbed dose rate (DR) and the average annual effective dose equivalent (AEDE) from all devices exceeded world standards. The radioactivity distribution showed higher dose rates resulting from higher radionuclide presence in various types of samples collected from different geologically potential areas. Increased dose rates evident at the northern side of the building is probably from the combined effect of various radioactive samples, uncovered old mosaic floor and radon in air concentration in old storage.
Key Words: Spatial distribution, Occupational worker, Radiation exposure, NORMs, Annual effective dose, Gamma survey meters, ALARA
Volume 14- Issue 02 | Year of Publication: 2026
Article type: Research Article | No. 89, 2026 | Country: Bangladesh | pp. 897-920 | Open Access
Title: IoT Technology Adoption in Agriculture: Investigating the Barriers in Bangladesh Conditions
Authors: Joy Biswas, Tanjidul Hasan, Surajit Sarkar, Mohd. Muzibur Rahman, Sahabuddin Ahamed, Chayan Kumer Saha, Md. Monjurul Alam
DOI: http://dx.doi.org/10.18801/jstei.140226.89
Title: IoT Technology Adoption in Agriculture: Investigating the Barriers in Bangladesh Conditions
Authors: Joy Biswas, Tanjidul Hasan, Surajit Sarkar, Mohd. Muzibur Rahman, Sahabuddin Ahamed, Chayan Kumer Saha, Md. Monjurul Alam
DOI: http://dx.doi.org/10.18801/jstei.140226.89
IoT Technology Adoption in Agriculture: Investigating the Barriers in Bangladesh Conditions
Abstract
The integration of Internet of Things (IoT) technology into the agriculture sector has the potential to transform farming practices and enhance agricultural productivity. Nowadays, the widespread adoption of IoT in agriculture is absent. The purpose of this study was to investigate the barriers to the adoption of IoT technology in the agricultural sector. Through literature review, KII, and expert opinions, 25 potential barriers were identified, and out of these, 11 key barriers were selected for further analysis. Besides that, 15 FGDs with farmers and 150 individual interviews were conducted. The Delphi method was employed for data collection, and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique was used to evaluate these barriers. The identified barriers include high investment requirements, lack of skills and aptitude, resistance to change, limited awareness among policymakers, inadequate digital communication infrastructure, absence of a regulatory framework, lack of a cohesive digital strategy, insufficient IoT training, gaps in knowledge management and data literacy, irregular maintenance and support, and limited understanding of IoT benefits. The study identifies the key factors by analyzing underlying interrelationships that influence the decision to adopt IoT in agriculture. The analysis revealed that resistance to change has the most significant negative impact on adoption, with a score of 1.13, while IoT training has the least negative impact, with a score of 0.39. The main barriers are high investment costs, a lack of training, and a clear understanding of IoT benefits, which are affecting adoption. These findings highlight the importance of addressing financial constraints, providing education and training, and increasing awareness among stakeholders to overcome key barriers and promote the adoption of IoT solutions for advanced agricultural practices.
Key Words: IoT, Adoption, Barrier, Technology, Agriculture
Abstract
The integration of Internet of Things (IoT) technology into the agriculture sector has the potential to transform farming practices and enhance agricultural productivity. Nowadays, the widespread adoption of IoT in agriculture is absent. The purpose of this study was to investigate the barriers to the adoption of IoT technology in the agricultural sector. Through literature review, KII, and expert opinions, 25 potential barriers were identified, and out of these, 11 key barriers were selected for further analysis. Besides that, 15 FGDs with farmers and 150 individual interviews were conducted. The Delphi method was employed for data collection, and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique was used to evaluate these barriers. The identified barriers include high investment requirements, lack of skills and aptitude, resistance to change, limited awareness among policymakers, inadequate digital communication infrastructure, absence of a regulatory framework, lack of a cohesive digital strategy, insufficient IoT training, gaps in knowledge management and data literacy, irregular maintenance and support, and limited understanding of IoT benefits. The study identifies the key factors by analyzing underlying interrelationships that influence the decision to adopt IoT in agriculture. The analysis revealed that resistance to change has the most significant negative impact on adoption, with a score of 1.13, while IoT training has the least negative impact, with a score of 0.39. The main barriers are high investment costs, a lack of training, and a clear understanding of IoT benefits, which are affecting adoption. These findings highlight the importance of addressing financial constraints, providing education and training, and increasing awareness among stakeholders to overcome key barriers and promote the adoption of IoT solutions for advanced agricultural practices.
Key Words: IoT, Adoption, Barrier, Technology, Agriculture
