Ul Hassan Hafiz Zameer, Wang Anyi, Mohi-Ud-Din Ghulam
College of Communication and Information Engineering, Xi'an University of Science and Technology, Xi'an, 710054, China.
Department of Computer Engineering - University of Florida, Gainesville, FL, USA.
Heliyon. 2024 Dec 24;11(1):e41262. doi: 10.1016/j.heliyon.2024.e41262. eCollection 2025 Jan 15.
Coal mining industry is one of the main source for economy of every nations, whereas safety in the underground coal mining area is still doubtful. According to some reports, there is heavy loss of life and money due to the occasional accidents in the coal mining area. Some existing researchers has been addressed this issue and approached their method. But the limitations are the communication range between the anchor nodes are weak because of its complex infrastructure. In coal mines, gas leaks pose a serious safety risk, often leading to explosions or toxic exposure. Temperature control is difficult due to fluctuating underground conditions, potentially causing heat stress or equipment malfunction. Real-time worker tracking is challenging in these environments, making it harder to monitor safety and respond swiftly to emergencies. To overcome the challenges, the proposed research uses modified precise DV (Distance Vector)-Hop localization algorithm. The data is collected from the nodes and it will generate as anchor nodes and sensor nodes. The proposed research includes some parameters to analyze the abnormal environment characteristics such as network parameters, proposed localization algorithm parameters, simulation parameters, safety monitoring parameters. These parameters helps to send the safety alert to the ground center in case of any emergency such as high temperature, gas leakage, changes in air humidity. The proposed model has the ability to detect all the sensor nodes within the threshold value as well as outside the threshold value. This shows that the proposed model communication range and it accuracy is higher than the existing research. The MATLAB simulation tool is used to enhance the localization of the proposed algorithm where, it is compare the traditional DV-Hop localization algorithm. The proposed algorithm attain high performance accuracy than existing method. The efficiency of the proposed modified precise DV-Hop localization algorithm is evaluated by the simulation outcomes.
煤炭开采行业是每个国家经济的主要来源之一，然而地下煤矿区的安全状况仍令人担忧。据一些报道，由于煤矿区偶尔发生的事故，造成了重大的人员伤亡和财产损失。一些现有研究人员已经探讨了这个问题并提出了他们的方法。但局限性在于，由于其基础设施复杂，锚节点之间的通信范围较弱。在煤矿中，瓦斯泄漏构成严重的安全风险，常常导致爆炸或有毒物质暴露。由于地下条件波动，温度控制困难，可能导致热应激或设备故障。在这些环境中，实时追踪工人具有挑战性，使得监测安全状况和迅速应对紧急情况变得更加困难。为了克服这些挑战，本研究采用了改进的精确距离向量（DV）-跳数定位算法。数据从节点收集，并将其生成锚节点和传感器节点。本研究包括一些参数来分析异常环境特征，如网络参数、提出的定位算法参数、仿真参数、安全监测参数。这些参数有助于在发生任何紧急情况（如高温、瓦斯泄漏、空气湿度变化）时向地面中心发送安全警报。所提出的模型能够检测阈值内以及阈值外的所有传感器节点。这表明所提出的模型通信范围及其准确性高于现有研究。使用MATLAB仿真工具来增强所提出算法的定位能力，在此将其与传统的DV-跳数定位算法进行比较。所提出的算法比现有方法具有更高的性能精度。通过仿真结果评估所提出的改进精确DV-跳数定位算法的效率。
