This work explores the optimum tensile strength and hardness of AISI 1018 low carbon steel plate welded joint using an E7018 electrode. The effect of metal metal arc welding process parameters namely; welding current and welding travel speed on AISI 1018 low carbon steel samples. The optimum performance of weld joints has been assessed based on the ultimate tensile strength and hardness of welded joints considering the welding current and travel speed variation. Taguchi-based L4 orthogonal array has been considered for the design of the experiment. The welding parameters on Tensile strength and Hardness of AISI 1018 low carbon steel plate welded joints were evaluated. The results show that there was no significant effect in current variation from 80A to 100A on the Ultimate Tensile strength and hardness of AISI 1018 low carbon steel plate with an average UTS and hardness of 434MPa and 122, respectively. However, it seemed that the welding travel speed of 20 to 21 mm/s, slightly affected the ultimate tensile strength and the hardness.

This research addresses the significant challenge of unreliable wireless communication, which hinders the performance of ZigBee-based wireless sensor networks (WSNs) in precision agriculture. A dual-slope log-distance path loss model was developed to accurately predict signal propagation complexities in dense vegetative environments for improved wireless communication. The study was conducted on a cassava farm in Ondo State, Nigeria, characterized by vegetation heights of 1.8 meters, making it an ideal site for investigation. A systematic methodology was employed, incorporating radio frequency measurements in both line-of-sight and non-line-of-sight conditions. This involved deploying two XBee S2C modules operating at 2.4 GHz, with one designated as a coordinator and the other as a router. The collection of Received Signal Strength Indicator (RSSI) and throughput data occurred at 5 meter intervals, with variations in the router's orientation. Results revealed a maximum communication range of 70 meters under non-line-of-sight conditions, compared to 140 meters in line-of-sight scenarios, where the path loss exponent was determined to be 1.78. The path loss exponents for the cassava fields were found to be 2.55 and 4.25. The developed dual-slope path loss model showed a strong fit to additional empirical data from a separate cassava farm location, achieving a Mean Absolute Percentage Error (MAPE) of 3.30 % and an R-squared value of 0.94. Hence, this model offers a comprehensive framework for characterizing radio wave propagation in agricultural environments, enhancing data transmission reliability and energy efficiency in smart farming applications.