The effects of climate change have altered precipitation patterns, causing extreme weather events that impact crop yields and increase the demand for agricultural production, which drives the need to implement emerging technologies. This research presents the design, construction, and validation of a real-time monitoring system for environmental parameters in open-field avocado orchards. A four-phase methodology was employed: (1) Establishment of required parameters and construction of the IoT architecture; (2) Design of the geometry and final elaboration of the system: modeling in SolidWorks, circuit diagrams in Fritzing, and system assembly; (3) Development of a mobile application: Android Studio and development of the autoencoder model with machine learning; and (4) Validation: Evaluation of the wireless link; system implementation and deployment of the mobile application. The results obtained include a system with a transmitter node equipped with sensors and a receiver, both incorporating ESP32 and nRF24L01+PA+LNA modules, with a wireless transmission range of 2300 m. A total of 2016 data records were stored on microSD and in the cloud, which can be queried, visualized, and analyzed through the mobile application via Bluetooth or Wi-Fi; the system also detects outlier data that can be used for decision-making in the agricultural sector.