REAL TIME MONITORING TECHNOLOGY APPROACH IN ELIMINATING UNCONVENTIONAL DATA TRANSMISSION RECESSION FOR ENVIRONMENTAL MONITORY
Abstract
ABSTRACT The study examined the real time monitoring technology approach in eliminating unconventional data transmission recession for environmental monitoring. Two objectives, two research questions and two hypotheses were formulated to guide the study. This study adopted a descriptive survey research design. The study was conducted in Rivers State. The population of the study comprised all 20 personnel from the Rivers State Ministry of Environment. A sample size of all the 20 Environmental Monitoring officers who are directly involve in environmental data collection, monitoring, and policy implementation (Senior 10 and Junior 10) were used because of the manageable size. The instrument for data collection was a structured questionnaire titled “Real-Time Monitoring Technology Approach for Environmental Data Transmission Questionnaire”. A Cronbach’s Alpha reliability test was conducted, yielding a reliability coefficient of 0.73, indicating a high level of reliability. A total of 20 copies of the questionnaire were administered to the selected personnel, and all were successfully retrieved. The collected data were analyzed using mean and standard deviation, while t-test statistics was used to test hypotheses at 0.05 level of significant. The study revealed that both Geographical Information Systems (GIS) and IoT sensors technologies are widely used in eliminating unconventional data transmission recession in environmental monitoring. Therefore, it was recommended among others that; environmental monitoring agencies should prioritize the adoption and integration of advanced GIS and IoT sensor technologies to improve real-time data collection, analysis, and decision-making.
Fields of Study & Subjects
Environmental Monitoring and Data Management
Arduino and IoT Applications
Air Quality Monitoring and Forecasting
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 15 March 2026
- Language
- EN