<![CDATA[Former mining lands in Indonesia, particularly in East Kalimantan, experience severe soil degradation characterized by high acidity, nutrient deficiency, and poor physical structure, which limit their potential for agricultural reuse. This study presents the design and implementation of an integrated Internet of Things (IoT)–based soil monitoring system combined with an artificial intelligence (AI)–driven crop recommendation module to support data-driven land reclamation and precision agriculture. The system consists of an ESP32 microcontroller, NPK soil sensors with RS485 communication, and a cloud-connected mobile application developed using Flutter, Firebase, and ThingsBoard. Soil parameters including pH, moisture, electrical conductivity, temperature, and macronutrients (nitrogen, phosphorus, and potassium) are collected in real time and analyzed using an AI-based reasoning model to generate crop suitability recommendations. System validation was conducted through black-box functional testing covering authentication, data acquisition, geotagged storage, analytics, and recommendation modules. A total of 35 test cases were executed, with 33 cases (94.3%) passing successfully. Performance evaluation shows that dashboard visualization and recommendation generation meet predefined service-level thresholds under normal network conditions. The results indicate that the proposed system is technically feasible for real-time soil monitoring and decision support on post-mining land. However, this study is limited to system-level validation and does not yet include large-scale agronomic field trials or comparative evaluation against conventional soil assessment methods. Future work will focus on improving AI model validation, expanding field deployment, and assessing agronomic impacts over longer cultivation cycles.]]>
