Studies on Propagation Characteristics of Radio Waves for Wireless Networks in Underground Coal Mines

Ranjan, Alok; Misra, Prasant; Dwivedi, Bharat; Sahu, H. B.

doi:10.1007/s11277-017-4636-y

Cited by 20 publications

(14 citation statements)

References 14 publications

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“…Another sharp technological problem is the development of connectivity solutions and propagation models in underground work sites, especially in the sector of coal mining, which is considered as one of the riskiest places of work due to the high probability of roof-falling, the concentration of toxic gases, explosions and so on. In this case, technology should cope with low-power signals, electrical interference, multiple reflections across the corners, and at greater depth [ 177 ]. The problem of the existing solutions like Wi-Fi, Zigbee, Bluetooth, cellular technologies lies in short communication distance and high delay [ 178 ].…”

Section: Challenges and Future Perspectivementioning

confidence: 99%

Wearables for Industrial Work Safety: A Survey

Svertoka

Saafi

Rusu-Casandra

et al. 2021

Sensors

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Today, ensuring work safety is considered to be one of the top priorities for various industries. Workplace injuries, illnesses, and deaths often entail substantial production and financial losses, governmental checks, series of dismissals, and loss of reputation. Wearable devices are one of the technologies that flourished with the fourth industrial revolution or Industry 4.0, allowing employers to monitor and maintain safety at workplaces. The purpose of this article is to systematize knowledge in the field of industrial wearables’ safety to assess the relevance of their use in enterprises as the technology maintaining occupational safety, to correlate the benefits and costs of their implementation, and, by identifying research gaps, to outline promising directions for future work in this area. We categorize industrial wearable functions into four classes (monitoring, supporting, training, and tracking) and provide a classification of the metrics collected by wearables to better understand the potential role of wearable technology in preserving workplace safety. Furthermore, we discuss key communication technologies and localization techniques utilized in wearable-based work safety solutions. Finally, we analyze the main challenges that need to be addressed to further enable and support the use of wearable devices for industrial work safety.

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Section: Challenges and Future Perspectivementioning

confidence: 99%

Wearables for Industrial Work Safety: A Survey

Svertoka

Saafi

Rusu-Casandra

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…These equations do not take into considerations the unique features of underground workings, e.g., side wall roughness and tilt of the ore body. Since the underground mine workings are quite different than the normal propagation environment, we refer the readers to some comprehensive articles in this particular topic where researchers have discussed in detail about the mathematical modeling of communication networks in underground mines [29], [47], [51], [52]. We do not provide such insights here as this topic is beyond the objective of this research work.…”

Section: ) Received Signal Strength Indicator (Rssi)mentioning

confidence: 99%

Opportunities and Challenges in Health Sensing for Extreme Industrial Environment: Perspectives From Underground Mines

et al. 2019

Self Cite

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Occupational health and safety hazards in the extreme work environment of underground mines remained a serious concern for both mine management and regulatory agency. Miners are often employed to perform different mining activities across the mine and are always exposed to health risks such as lung cancer. With the technology advancements, it is now possible to keep track of mine individuals and their health parameters. The current practice of health analysis is periodic in nature and is highly dependent on voluntary participation. Wearable health sensing system is an alternative solution to overcome these challenges and is able to provide insights on miners' health conditions. Timely analysis of physiological parameters of the miners is immensely helpful to minimize the injuries and can also provide preventive measures for potential health hazards. In this paper, we propose a wireless health monitoring system, especially for underground mines. The contributions of this paper are twofold. First, it presents and discusses our proposed system architecture and solution followed by challenges of such system in the context of underground mines. Second, as a preliminary analysis, detailed discussion on the wireless link behavior for reliable data transmission and communication are presented. We performed real-world experimental measurements in an operational underground coal mine considering several deployment settings in straight, near face and curved mine galleries. The communication metrics (e.g., received signal strength and packet reception rate) are extensively evaluated.INDEX TERMS Health sensing, activity monitoring, underground mines, occupational health hazards, communication, data analytics, wearables in mines, artificial intelligence, miners.

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“…Coal with high resistivity has weak absorption of electromagnetic waves, which is beneficial to its penetration. The anomalous structures with lower resistivity, such as faults, collapse columns, and voids, have stronger shielding effects on electromagnetic wave absorption, resulting in significant energy attenuation [22][23][24]. Therefore, the distribution of abnormal structures within the working face can be predicted by analyzing the variation of electromagnetic field intensity in the working face.…”

Section: Inversion Modelmentioning

confidence: 99%

Application of an Adaptive Multi-Population Parallel Genetic Algorithm with Constraints in Electromagnetic Tomography with Incomplete Projections

Guo

Yang

et al. 2019

Applied Sciences

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Electromagnetic tomography technology (EMT) is widely used in underground energy exploration. Limited by objective conditions, the collected projection data of electromagnetic waves are sparse and incomplete. Therefore, a study of the tomographic inversion algorithm of EMT based on incomplete projection data has an important guiding significance for the exploitation of underground energy. As a global optimization probability search algorithm, the simple genetic algorithm (SGA) has been widely used in the process of tomographic inversion. However, SGA evolves through a single population, and the values of crossover and mutation probability are always fixed, so there are risks of premature convergence and poor local search ability. To improve the performance of the SGA, a new approach of adaptive multi-population parallel genetic algorithm (AMPGA) with constraints is proposed in this paper. First, the AMPGA makes full use of multi-group adaptive co-evolution to improve the local and global search ability of SGA and restrain the risk of premature convergence. Then, the introduction of prior information as a constraint makes the results clearer and more accurate. The proposed algorithm has been verified in a numerical experiment and field tests, and the results show that the proposed algorithm can well balance global and local search capabilities, which offers a more realistic and stable tomographic result.

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Studies on Propagation Characteristics of Radio Waves for Wireless Networks in Underground Coal Mines

Cited by 20 publications

References 14 publications

Wearables for Industrial Work Safety: A Survey

Wearables for Industrial Work Safety: A Survey

Opportunities and Challenges in Health Sensing for Extreme Industrial Environment: Perspectives From Underground Mines

Application of an Adaptive Multi-Population Parallel Genetic Algorithm with Constraints in Electromagnetic Tomography with Incomplete Projections

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