Among the undesirable effects of soil compaction is a measurable reduction in plant growth and crop yield. The prevailing belief is that compacted tillage pans are caused by repetitive farming practices, heavy tractors, tillage tools, and field traffic. This experiment was conducted to determine and map the hardpan layers across an agricultural field through advanced technologies of precision agriculture. These valuable techniques such as data logger, yield map, and data analysis of performance indicators were linked with accurate global positioning systems (GPS) datasets. These important technologies provided the farmers and helped them to identify and manage areas of the fields with higher compacted layers. Three ground speeds 4.3, 5.2, and 6.4 km h-1 were performed with two tillage depths 25 and 40 cm of a chisel plow. The effects of these two factors were studied to determine slippage percentage, field productivity, traction power, and fuel consumption. For the first shallow 25 cm depth, the results showed that increasing the speed from 4.3 to 5.2 and then to 6.4 km h-1 led to a significant increase in slippage percentage from 7.22 to 10.35 and then to 12.63%, respectively. Increasing the speed increases field productivity from 0.547 to 0.663 then to 0. 749 ha hour-1, and tractive power increases from 9.44 to 11.74, then to 13.24 hp. As a result, there was a significant increase in the fuel consumption rate from 18.44 to 20.15, then to 22.27 L hour-1, respectively. Changing the depth from 25 to 40 cm and increasing the practical speed from 4.3 to 5.2 and then to 6.4 km h-1 led to a significant increase in slippage percentage from 10.14 to 12.77 and then to 15.27%, and a significant increase in field productivity from 0.446 to 0.568 and then to 0.640 ha hour-1, respectively. This led to a significant increase in traction power from 12.72 to 13.36, then to 15.87 hp. Increasing the speed also brought a significant increase in fuel rate from 22.14 to 23.54 and then to 26.14 L ha-1, respectively. Based on this study, it was concluded that the use of this powerful approach was a useful methodology to reflect, determine, specify, and manage the regions of induced and hardpan zones by means of dataset analyses provided by the GPS for the desired field.