Abstract
The Internet of Things (IoT) has orchestrated various domains in numerous applications, contributing significantly to the growth of the smart world, even in regions with low literacy rates, boosting socio-economic development. This study provides valuable insights into optimizing wireless communication, paving the way for a more connected and productive future in the mining industry. The IoT revolution is advancing across industries, but harsh geometric environments, including open-pit mines, pose unique challenges for reliable communication. The advent of IoT in the mining industry has significantly improved communication for critical operations through the use of Radio Frequency (RF) protocols such as Bluetooth, Wi-Fi, GSM/GPRS, Narrow Band (NB)-IoT, SigFox, ZigBee, and Long Range Wireless Area Network (LoRaWAN). This study addresses the optimization of network implementations by comparing two leading free-spreading IoT-based RF protocols such as ZigBee and LoRaWAN. Intensive field tests are conducted in various opencast mines to investigate coverage potential and signal attenuation. ZigBee is tested in the Tadicherla open-cast coal mine in India. Similarly, LoRaWAN field tests are conducted at one of the associated cement companies (ACC) in the limestone mine in Bargarh, India, covering both Indoor-to-Outdoor (I2O) and Outdoor-to-Outdoor (O2O) environments. A robust framework of path-loss models, referred to as Free space, Egli, Okumura-Hata, Cost231-Hata and Ericsson models, combined with key performance metrics, is employed to evaluate the patterns of signal attenuation. Extensive field testing and careful data analysis revealed that the Egli model is the most consistent path-loss model for the ZigBee protocol in an I2O environment, with a coefficient of determination (R
2) of 0.907, balanced error metrics such as Normalized Root Mean Square Error (NRMSE) of 0.030, Mean Square Error (MSE) of 4.950, Mean Absolute Percentage Error (MAPE) of 0.249 and Scatter Index (SI) of 2.723. In the O2O scenario, the Ericsson model showed superior performance, with the highest R
2 value of 0.959, supported by strong correlation metrics: NRMSE of 0.026, MSE of 8.685, MAPE of 0.685, Mean Absolute Deviation (MAD) of 20.839 and SI of 2.194. For the LoRaWAN protocol, the Cost-231 model achieved the highest R
2 value of 0.921 in the I2O scenario, complemented by the lowest metrics: NRMSE of 0.018, MSE of 1.324, MAPE of 0.217, MAD of 9.218 and SI of 1.238. In the O2O environment, the Okumura-Hata model achieved the highest R
2 value of 0.978, indicating a strong fit with metrics NRMSE of 0.047, MSE of 27.807, MAPE of 27.494, MAD of 37.287 and SI of 3.927. This advancement in reliable communication networks promises to transform the opencast landscape into networked signal attenuation. These results support decision-making for mining needs and ensure reliable communications even in the face of formidable obstacles.
Keywords
Internet of things; long range wireless area network; ZigBee; mining environments; path-loss models; coefficient of determination; mean square error
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