Agriculture Development

This study aimed to design and implement a low-cost microcontroller-based system for monitoring the energy consumption of individual workshop machines, addressing the limitations of conventional centralized metering systems that fail to provide machine- specific data. The literature review examined previous work on energy monitoring technologies, including commercial, open-source, and academic systems, highlighting the growing role of the Internet of Things (IoT) in enabling real-time data acquisition and remote monitoring. It emphasized the need for affordable, scalable, and educationally adaptable solutions for developing regions, where technical expertise and financial resources are limited. The research adopted an experimental design methodology involving hardware and software integration. The system was built using Arduino Nano and ESP32 microcontrollers, ZMPT101B voltage and SCT-013 current sensors, an LCD display, and a ThingSpeak IoT cloud interface. Mathematical modeling was applied to compute voltage, current, power, energy, and cost, while SolidWorks was used for casing design. Calibration and testing were conducted under varying load conditions to assess accuracy, response time, and data stability. Data were logged both locally on an SD card and remotely on the cloud for redundancy and analysis. Results indicated that the system achieved high accuracy within ±1% for voltage and ±5% for current, with an overall efficiency of 95% and IoT data transfer uptime of 98%. The developed prototype successfully provided real-time monitoring, stable performance, and reliable data transmission. The study concluded that the Arduino-based energy monitoring system is a cost-effective, scalable, and efficient solution suitable for educational, domestic,v and small-scale industrial applications. It recommended future enhancements in predictive analytics, multi-machine scalability, and integration with renewable energy management platforms.

This research studied the role of local government administration on rural agriculture and health development in Delta central senatorial district, Delta State, Nigeria. The specific objectives are to; ascertain the extent local government have ensured rural development; identify the programmes and projects put in place by local government for rural development; and to identify the constraints hindering local government towards rural agriculture and health development in the study area. A multi-staged sampling technique was adopted in the selection of respondents in the study. Data for the study were obtained from both primary and secondary sources. Primary data were obtained through the use of a structured questionnaire administered to eighty (80) selected respondents in the study area through interview schedule. Data obtained were measured and analyzed using descriptive statistics while the hypothesis testing was analyzed using Pearson’s Product Moment Correlation (PPMC). Result showed that over 63.7% of the sampled respondents consist of an aging population whose age ranges from fifty-one (51) and above while majority (73.3% and 93.7%) of the sampled respondents are female and married respectively. About 39% of the sampled respondents had no formal education, while 61.2% had at least primary education. The sampled respondents had an average household and family size of five (5) and seven (7) respectively- an indication that family members remain the primary source of labour. Furthermore, respondents indicated significant satisfaction with local government health development programmes- construction of healthcare facilities, supply of medicine and vaccines, address health workers shortage and improved health care accessibility and dissatisfaction with all agriculture development programmes put in place by local government administration in the study area. Result of Pearson’s Product Moment Correlation (PPMC) showed significant relationship between selected socio-economic 9 characteristics and respondents’ satisfaction with local government administration on rural agriculture and health development programmes at 5% and 1% level of probability