Multiple linear regression and the United States Bureau of Mines (USBM) empirical techniques are also conducted to compare with nine developed ANN models. In this study, nine artificial neural networks (ANN) models were developed to predict blast-induced PPV in Nui Beo open-pit coal mine, Vietnam. ![]() The principal object of this study is blast-induced ground vibration (PPV), which is one of the dangerous side effects of blasting operations in an open-pit mine. Required parameters have been measured using the LoRa WAN technology at 2.4 GHz frequency. Transmission-reception in a non-line of sight (NLOS) condition. In this article, an endeavor has been made to introduce a LoRa WANĬonnectivity and proved the potentiality of the integrated WSN paradigm by testing of data Wirelessly deliver the information to mine management and surrounding rural peoples to aware of Long-Range (LoRa) Correct as Radio Frequency (RF) module, construct a WSN configurationįor acquisition and streaming of required data from and to an IoT gateway. Low-power wide-area networks (LPWANs) based system. Thus, proposed and developed an architecture which emphasizes the IoT realm and implements a It is an indispensable prerequisite for measuring theīlast-induced ground vibration (BIGV), accomplishing a topical and most active research area. Ground vibration can be induced by blasting demolition is a severe concern which grievouslyĭamages the nearby dwellings and plants. Seamless transfer of information via embedded computing and network devices. Of Things (IoT) vision enables a variety of low-cost monitoring applications which allows a The recent proliferation of wireless sensor networks (WSNs) evolution into the Internet Obtained results were compared based on correlation of determination (R²) and standard error between recorded and predicted values of PPV. A three-layer, feed-forward back propagation neural network consists of 6 input parameters, 5 hidden neurons, and one output parameters were trained. The results are very promising and the recorded PPV varies from 0.191 mm/s to 8.60 mm/s. The data has been transmitted by ZigBee (IEEE 802.15.4) protocol. Eleven blasts PPV were recorded at different locations using wireless sensor network prototype system. ![]() In this paper, an attempt has been made to monitor the BIGV with low-cost wireless sensor network (WSN) and prediction of peak particle velocity (PPV) using an artificial neural network (ANN) technique at ACC Dungri limestone mine, Bargarh, Odisha, India. ![]() Usage of a high amount of explosive causes ground vibrations that are harmful to the nearby habitats and dwellings. Blast-induced ground vibration (BIGV) is an undesirable environmental issue in and around mines.
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