This research is focused on designing and building a reliable wireless sensor network (WSN) system to monitor and collect data such as humidity, air pressure, and soil moisture parameters in the agricultural domain. This system will be allow for data-logging and data-analysis services by using techniques in WSN and machine-learning algorithms. We believe that by applying advanced WSN technology to collect real-time data in the field and extract features from raw data, farmers can gain more insights into crop growth and lower production costs. Currently, we are focusing on the irrigation part inside the agricultural domain and building WSNs using Mica nodes. The sensor nodes will collect barometric pressure, light, humidity, and temperature data. We hope to use the collected data for further analysis, which can be used to set the triggers of real-time alarm systems in the field.