<![CDATA[The monitoring of material transport vehicles in stone crusher production is commonly performed manually, resulting in delays in information delivery, inaccuracies in vehicle records, and increased production downtime caused by late material supply. This study aimed to design and develop an Internet of Things (IoT)-based material vehicle monitoring system using an ESP32-CAM to support the stone crusher production process. The proposed system integrates two ultrasonic sensors to detect the direction of vehicle movement, an ESP32-CAM to capture vehicle images, a DHT11 sensor to monitor the temperature inside the enclosure, and the Telegram application to deliver real-time notifications and monitoring information. The research consisted of hardware and software design, system implementation, functional testing, and statistical analysis. Experimental data were analyzed using descriptive statistics and an Independent Samples t-test after satisfying the assumptions of normality and homogeneity to evaluate the effect of Wi-Fi network speed on data transmission time. The results showed that the developed system successfully detected incoming and outgoing vehicles with a 100% detection accuracy and automatically transmitted vehicle images and information to Telegram. The average data transmission time was 3.0139 s using a 10 Mbps Wi-Fi network and 1.7130 s using a 50 Mbps Wi-Fi network. Statistical analysis indicated that Wi-Fi network speed had a significant effect on data transmission time (p < 0.05). Furthermore, the implementation of the proposed system reduced production downtime caused by delayed material supply from 60 min to 10 min per day, representing an 83.33% reduction. These findings demonstrate that the developed IoT-based monitoring system improves vehicle recording accuracy, accelerates information delivery, and supports more efficient production operations in the stone crusher industry.]]>
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