IntroductionThe U.S. approach to health and safety in mining has historically been reactive in the sense that health and safety regulations and mandates have traditionally been passed as a result of tragic mining accidents. An example of this is the Mine Improvement and New Emergency Response Act (MINER Act) of 2006, which was passed as a result of several mining accidents where tracking of and communication with underground personnel were severely limited. While this reactive approach has led to the development and implementation of highly impactful safety interventions and safety practices, there exists a technological revolution that can shift the paradigm toward a proactive approach based on preventative methods: Internet of Things (IoT).
IoT is the network of physical objects, or “things,” embedded with electronics, sensors and connectivity to enable that network to achieve greater value and service by exchanging data with the manufacturer, operator and/or other connected devices (Atzori, Iera and Morabito, 2010; Gubbi et al. 2013). It should be noted that IoT has been defined from various perspectives, and hence numerous definitions exist in the literature. The apparent ambiguity of the IoT definition might be due to the fact that IoT is syntactically composed of two terms: the Internet and things. The first word pushes toward a network-oriented vision, while the second tends to put the focus on generic objects. The traditional Internet can be viewed as an internet of computers, so things connected to the Internet are computers only. IoT extends the internet by allowing other generic things that are commonly found in daily life, such as refrigerators and cars, to be interconnected through the Internet, thus creating a bridge between the virtual world and the physical world.
According to Gartner’s 2014 Hype Cycle (Gartner Inc., 2014), IoT was the most hyped emerging technology of the year. Companies such as Amazon, General Electric, Microsoft and IBM heavily investigated IoT and now offer commercially available IoT platforms to a variety of industries. Terms used to represent the concept of IoT include Internet of Everything (IoE), Industrial Internet, Industry 4.0 and Web of things (WoT).
Currently, many IoT technologies are integrated into consumer applications, such as smart homes, connected cars and smart wearables. The industrial applications of IoT, or Industrial IoT (IIoT), however, is anticipated to have the capability to transform many industries, including manufacturing, oil and gas, agriculture, and mining.
With advances in sensing technologies, more and more sensors are being deployed in underground mines to measure important operational and environmental parameters such as carbon monoxide concentration, methane concentration, airflow, temperature and belt-running conditions. They collect a massive volume of data daily. One challenge is processing the data to best improve mine safety and operational efficiency. Combining IIoT and Big Data analytics offers a unique solution to this challenge and is expected to bring unprecedented opportunities to the mining industry.
Though not under the term IIoT, the mining industry has been deploying programmable logic controller (PLC) and supervisory control and data acquisition (SCADA) systems for monitoring and controlling for decades. For example, there exist a number of commercially available U.S. Mine Safety and Health Administration (MSHA)-approved wireless atmospheric monitoring systems (AMS) for coal-mining applications. There are also some wired monitoring systems, such as the PLC-controlled AMS network systems from Conspec Controls (Charleroi, PA). Compared with IIoT systems, these existing monitoring and control systems are generally proprietary systems and were not designed to interoperate or interconnect with other systems. The major difference between IIoT-based systems and legacy monitoring systems is that IIoT systems are based on an open, highly connected Internet Protocol (IP) network structure. Transition to the more open network architectures and data sharing of IIoT may bring opportunities to the mining industry that will enable it to move toward the next generation of smart mining and automation.
While the health and safety implications of applying IIoT technologies go well beyond mining, introducing these technical advancements into the underground coal mine environment may be especially challenging, and there are specific considerations that must be taken into account to transfer concepts to mining in general. This paper provides theories and applications essential to accelerate the adoption of IIoT at underground mines, discusses the feasibility, potential and challenges for underground coal mines, and presents a practical example of a mining-specific application.
IIoT in the mining industry: State of the market and related workIIoT in metal/nonmetal minesDue to the current economic climate in mining, mine operators are heavily focused on improving asset management and equipment life-cycle management, and minimizing production costs. A report by Accenture (2015) said these priorities may open the door to IIoT in mining and revealed that 79 percent of the mining companies surveyed identified investing in data analytics and Industrial Internet as among their top three priorities.
The worldwide mining industry is already leveraging IIoT in wireless mining automation and connected mine projects. For example, Rio Tinto (2008) has been using autonomous, self-driving mining trucks to move ore around since 2008. Each self-driving truck has more than 200 sensors, a GPS receiver and a radar guidance system. The fleet is managed from an operations center located more than a thousand miles away. At the operations center, data from the vehicles and other equipment are fed into a comprehensive mine automation system, which gives a system view of the entire mining operation, including 3D visualizations of work sites and predictive maintenance schedules.
Cisco has actively promoted two cases where IIoT technology has been successfully applied to improve the safety and efficiency of underground mines. In the first case, which is perhaps one of the best known IIoT mining examples and has been highlighted in Cisco’s IIoT initiatives (Cisco, 2014), 280 Cisco wireless access points were installed in the flagship gold mine of Dundee Precious Metals in Chelopech, Bulgaria, to provide wireless coverage along 50 km (31 miles) of tunnels. The IIoT solution implemented at this mine has helped to connect people, track the locations of miners and vehicles, monitor vehicle status and automate building controls. In addition, the blasting system of the mine is connected to the personnel location tracking system to improve miner safety. The second case was presented through a partnership with Goldcorp (Cisco, 2015). In addition to communication and real-time tracking of people and assets, ventilation on demand (VoD) was implemented based on a multiservice IP network installed in one of Goldcorp’s mines.
In 2014, General Electric teamed up with mining equipment manufacturer Komatsu to implement IIoT solutions to improve the efficiency and service of mining operations (Vella, 2015). A joint venture called Komatsu and GE Mining Systems LLC was established to develop the next generation of mining solutions where IIoT and Big Data analytics are anticipated to play an important role. For example, the GE Remote Monitoring & Diagnostics technology can be used to provide data analytics on truck performance to prevent unnecessary maintenance events and, by extension, reduce the costs associated with replacing failed components and maintenance downtimes through automation of predictive maintenance schedules.
Engineers from the NTT Innovation Institute Inc. and Colorado School of Mines recently completed a pilot project using IIoT to provide VoD at the Edgar Experimental Mine (NTTi3, 2016). Based on the team’s assessment, the program achieved 10 percent energy savings in the first two weeks.
IIoT in coal minesWhile IIoT solutions have been successfully implemented in metal/nonmetal mines, the application of such technology in coal mines has been limited. Some barriers to IIoT integration in coal mines may be attributed to intrinsic safety requirements enforced in underground coal mines, the complexity of integrating full coverage into a mine infrastructure, and the initial overhead costs associated with integrating sensor networks and automation. Despite these barriers, some manufacturers and mine operators have taken initial steps to explore IIoT in underground coal mines.
Although still in its infancy in terms of implementation, IIoT in coal mines has been a hot research topic since early 2000 and has been widely investigated in China. For example, IIoT has been proposed in China for coal mine disaster warning (Hu et al., 2014), intelligent mine monitoring (Hu et al., 2013), mining equipment management (Tan et al., 2013), environmental sensing (Chen et al., 2012), real-time positioning (Wang, Zhou et al., 2011), coal seam water monitoring (Meng, Wang and Gao, 2012), and accident analysis (Sun, 2015). In addition to specific applications, some published papers focus on IIoT system overview and architecture design (Ke, 2010; Wei, Zhu and Du, 2011; Wang, Zhao et al., 2011; Zhang et al., 2012).
Reports on studies of IIoT in coal mines in other countries have been limited, but some related studies, such as those on minewide monitoring systems, have been reported in the United States and abroad. For example, the U.S. Bureau of Mines (1984) published a technical report comparing different mine monitoring systems in underground mines, and Nutter and Aldridge (1988) investigated the status of mine monitoring and communication. More recently, U.S. National Institute for Occupational Safety and Health (NIOSH) researchers conducted an MSHA data survey and found that 204 carbon monoxide systems and 33 AMS systems had been installed in producing coal mines in the United States (Rowland, III, Harteis and Yuan, 2017). Mine monitoring is a part of the IIoT, though it does not encompass the concepts of a complete IIoT solution on its own.
NIOSH has conducted intramural research in areas directly related to IIoT technologies. One of the key elements of underground IIoT is the communication backbone for connecting things underground. In 2010, NIOSH launched a five-year research project to investigate radio propagation mechanisms for the different frequencies that are commonly used by existing underground communications and tracking systems. Theoretical models were developed to predict underground communication and tracking system performance and were validated through extensive measurement results (Zhou, Waynert et al., 2015; Zhou, Plass et al., 2013).
In 2014, NIOSH engineers reviewed the emergency response plans of 306 active coal mines in the United States as part of a project on communication and tracking. The mines’ post-accident communication and tracking system installation information was extracted and analyzed (Damiano, Homce and Jacksha, 2014). One of the major results (Fig. 1) was a comprehensive overview of the communication and tracking systems installed in U.S. underground coal mines in 2014. The list was used to evaluate the state of post-accident communication and tracking systems being used throughout the United States and to explore the capabilities and limitations of these systems in handling the data transmission and infrastructure required to operate an IIoT network.
Feasibility of IIoT in coal minesTo answer the question of whether it is feasible to implement IIoT technologies in coal mines, one must understand the major components of IIoT systems and compare them with those that already exist in coal mines. By examining the IIoT technologies used in other industries, the following system core components are identified: (1) things, such as machines and people equipped with sensors, services and actuators, (2) networks, to connect things together, and (3) systems/platforms, to process data from/to things, often deployed in the cloud.
System of systemsIIoT comprises a large scale of smart things and is often referred to as a “system of systems.” Figure 2 shows some examples of existing underground systems that can potentially be integrated to form a new IIoT system.
Ventilation and fire detection systemsFires and explosions have been serious safety concerns since the advent of mining. Ventilation systems are crucial for maintaining nonexplosive and nontoxic atmospheres. The progression of technology has allowed mine monitoring techniques to become more sophisticated, and various advanced sensors for monitoring dust, oxygen, methane, carbon monoxide, carbon dioxide, temperature and air velocity have been developed and deployed throughout the mining industry (Rowland, III, Harteis and Yuan, 2017). In an IIoT system, these sensors could potentially be connected to a network to form a minewide monitoring system capable of collecting data and automatically transferring it to the surface through the existing communication backbone. The data can then be used to provide decision-making information and automatic actions. If an abnormal condition is detected, the local sensor node could be configured to simultaneously set off an alarm locally and in the monitoring and control center on the surface. Depending on the conditions detected, the system would then enact automatic measures to mitigate the hazard. For example, if the sensor data indicate a fire is occurring underground, the system may automatically activate fire suppression systems in the point of origin while taking additional measures to prevent the fire from spreading.
Personnel and asset tracking systemsWith the increasing mining equipment and assets — such as boring machines, shearers, conveyors, hydraulic support, hydraulic pump stations, loaders, crushers, motor vehicles, ventilation fans and water pumps — used in underground mines, equipment management systems are often needed to provide a more convenient, efficient and secure resource management platform. Through an IIoT network, the locations of those important assets along with the locations of all underground personnel can be tracked. As mandated by the MINER Act, all U.S. underground coal mines now have installed wireless tracking systems to track the locations of underground personnel. Many of those systems are based on radio-frequency identification (RFID) technologies, and thus can be easily incorporated into the proposed IIoT network platform.
SensorsTo get an overview of legacy sensors used in underground coal mines, sensors approved for use in U.S. underground coal mines during 1996 to 2016 were examined. It was found that the major MSHA-approved sensors are gas sensors, including those for methane, oxygen and carbon monoxide; airflow sensors; temperature and humidity sensors; vibration sensors; smoke sensors; and alarm sensors. There also exist approved sensors for monitoring other parameters, such as ventilation fan speed, pump water level, power status, and conveyor-belt conditions like speed and slip detection.
NetworksInformation collected by underground sensors should be readily accessible by underground miners as well as by dispatch personnel on the surface. Many mines have installed communication systems that have data back-haul capability. In these cases, an IIoT network may potentially be established based on existing mine communication systems, such as fiberoptics systems, leaky feeder systems, and node-based systems. IIoT systems likely require a large communication bandwidth to support the transmission of the massive amount of data collected underground. Therefore, from the bandwidth point of view, node-based systems with fiberoptics as a communication backbone would be favorable for IIoT applications. In addition, a communication interface between the existing communication backbone and the sensors would need to be established. One way to accomplish this is to attach a radio-frequency transceiver module to the sensors, or things. Different communication protocols, such as Wi-Fi, Zigbee, Bluetooth and BLE, should be investigated to identify the best protocol suited to underground mining applications.
As implied in the name, the Internet is one of the key components of IIoT technologies. Although low-power, IIoT-dedicated networks have been developed, deploying a new network underground may be costly. A solution would be to leverage existing communication and tracking networks as the backbone for these installations. As depicted in Fig. 1, there are a number of communication systems that may be suitable for sensor data transmission and controls. An examination of each of these systems found that five of 12 systems, or 42 percent, have the capability to provide Internet to the underground with little or no modification. The five Internet-capable communication system manufacturers in active U.S. underground coal mines are listed in Table 1.
The number of manufacturers and availability of Internet-ready systems may have increased since 2014, and additional technology review efforts may be required to obtain the most current data.
PlatformsPlatforms are responsible for analyzing data, collected in real time through modern high-performance computing systems, and delivering optimized recommendations to operators and other type of users both inside and outside of mines. By leveraging a customizable and intuitive user interface, and with full mobile accessibility, users are able to gather insight into mine safety and profitability over time. Platforms also make it possible for appropriate users to analyze historical and real-time data to deliver predictions or forecast disaster. Big Data analytics is increasingly becoming a critical component of IIoT in many industries, including mining. Applying Big Data analytics and predictive analytics effectively to the mining industry, based on the proposed IIoT network platform, can have a significant impact in the industry by processing massive amounts of data and streamlining the prioritization, automation and resolution of day-to-day operations and mine hazards encountered.
IIoT for real-time monitoring and control: Practical examplesTo show the feasibility and potential of IIoT for mining applications, an IIoT prototype system using commercially available components was built and demonstrated in NIOSH’s experimental mine in Pittsburgh, PA.
System descriptionAs shown in Fig. 3, the developed IIoT system consisted of IIoT sensors, a communication network, a cloud-based data engine and actuators. Some examples of IIoT sensors and the actuator, built specifically for this application, are shown in Fig. 4. These IIoT sensors were constructed by integrating the corresponding sensor with an ESP8266 miniature low-cost microcontroller board that had embedded Wi-Fi connectivity (Espressif Systems, Shanghai, China). The IIoT control unit (actuator) in Fig. 4 consists of a Wi-Fi microcontroller board, similar to what would be used in IIoT sensors, and a power switch controlled by the WiFi microcontroller board. For this demonstration, the Wi-Fi coverage underground was achieved by using an integrated cellular repeater system. The cellular signal coverage was extended from the surface to the underground work area using a cellular amplifier. The input antenna of the cellular amplifier was placed on the surface and connected to the amplifier located underground by a long, low-loss coaxial cable through a borehole. Any system that can be connected to the Internet with an open protocol could have been used in place of the cellular repeater system here.
Refuge alternative door-open detectionTo demonstrate the monitoring and control ability of the developed IIoT system prototype, a door-open detection sensor was installed to monitor the door status of a built-in-place refuge alternative located in the experimental mine. The sensor/micro-controller was programmed to conserve battery power, so it was dormant most of the time and would only transmit data whenever a door-open event was detected. The user interface would display the status of the door after it received messages from the sensor. A similar approach was taken for other controlled devices.
In this demonstration, one warning light and two fans were used to demonstrate the automatic actions enabled by the sensor network (Fig. 5). The actuators and sensors communicated with the server using the Message Queue Telemetry Transport (MQTT) protocol, which is a publish-subscribe lightweight messaging protocol designed for machine-to-machine communications. This messaging protocol is designed for small-code-footprint applications where the network bandwidth is limited. The system was programmed to activate a light and two fans when the refuge-alternative door was open and turn them off when the door was closed.
Although a simple door-open detection sensor was used in the demonstration, other sensors can also be used as the event triggers. The system can be configured to control one device with triggers from multiple sensors or to control multiple devices using a trigger from one sensor. Because the Internet is a worldwide network, the connected things in this demostration can essentially be monitored and controlled anytime, from anywhere in the world where there is Internet coverage. Even though the information can be accessed anywhere in the world, it could also be made local or even intranet-based, so only people with access to those intranet systems can get the information.