5G+AI to assist smart, safe mining

Since the beginning of the year, the eruption of energy crises in certain parts of the world have gained global traction. To offset energy shortages, increases in coal consumption have been consecutive and considerable. 

Many analysts believe that coal-generated power may well be on course to creating all-time highs for the second year in a row. It is against this backdrop that the coordinated development between coal-generated power and that from non-fossil fuels is expected to be highlighted at the ongoing climate talks in Egypt. 

Coal mine operations require a lot of people on site, for work that is fairly complex and dangerous. In the past month alone, there have been a number of reports of fatal mining accidents worldwide. 

For China, a country with some 5,300 mines and 1.3 trillion tonnes of proven coal reserves, recent practices in facilitating smart mining through an Industrial Internet Architecture embedded with 5G, artificial intelligence and basic research may have offered food for thought in the pursuit of safe, smart, efficient and green mining. Indeed, 5G and AI have cut across production processes from mining itself to tunneling and transport. 

Dust is unavoidable in the fully mechanised mining face, where the work environment is harsh. While remote controlled mining has become an industry consensus, a big challenge lies in the clear and real-time visualisation. 

Today, the ultra-high bandwidth of 5G networks and the reversed uplink-downlink timeslot configuration technology support wireless backhaul of HD videos with hundreds of channels in real time, with the uplink bandwidth up to over one Gbit/s. Using the AI technology and video stitching algorithm, separate images are combined into a panoramic one. 

Additionally, the dust-filtering algorithm helps ensure real-time HD videos of moving shearers, even when shrouded in dust and mist, can clearly show the working environment around shearers within a radius of 20 m. So now, the low latency of 5G networks helps ensure remote and precise control of mining machines, which enables people working underground to remotely control operations at offices. 

Underground tunneling is the most difficult and dangerous of all coal mine operations. Accidents during tunneling account for more than 40 percent of all coal mine accidents. In traditional mines, underground safety relies on manual efforts, such as team leaders supervising team members. That makes comprehensively identify and control risk elements highly improbable, in an area where more than 50 percent of tunneling accidents are attributed to human error.

With 5G backhauling real-time onsite video while AI algorithms track and detect underground operations, real-time alarms could be triggered when violations and quality issues are detected, ensuring operations safety from a technical standpoint. 

While transporting, belt conveyors are the main transport mode of coal mines. But they have been inefficient. A conveyor system, which is 20 km long or more needs almost 20 inspection staff. 

With 5G backhauls real-time video of the main transportation belt and AI algorithms accurately identifying anomalies, the system turns time-phased manual inspections into 24/7 intelligent monitoring and cuts the number of underground inspection personnel by 20 percent. 

On the equipment side, underground production involves more than 1,000 types of devices. Nearly half of them do not support remote control centralized control or remote management. These devices use over 10 types of operating systems, 500 types of interface protocols and various data formats. Their operations are complicated and inefficient and no interconnections or interoperations are available. 

Then came MineHarmony, an operating system that unified device languages, simplified operations and unattended inspections. The system covers devices of all sizes and uses unified protocols, to enable data sharing between devices, human-machine interconnections machine-machine interconnections and ambient awareness. 

Based on comprehensive real-time data the command and dispatch personnel monitor mining operations, from above ground and intelligently dispatch tasks in real-time, allowing safer and more efficient production. For example, the command and dispatch center can detect incidents, such as gas overflows, organize an evacuation, shut down mining equipment and ventilate the site in a timely manner boosting emergency response efficiency. 

Looking on, powered by achievements in math, physics and other basic research areas, 5G + AI will be applied in more mining scenarios. Expert experience will be summarised into AI algorithms to free people from hazardous, complicated, and repetitive work. For example, during the operations for pressure relief and rock burst prevention, AI-based video analysis will help intelligently detect the drilling depth, enabling traceable quality and controllable processes while safeguarding the underground production environment. 

“Mining must grow for the foreseeable future. The whole purpose is not to kill industries that provide jobs for millions of workers but rather to transform production and consumption onto a path that will be more sustainable and green. It is clear that in the post-pandemic world, Digital Technologies (DT) will help to resuscitate the global economy by accelerating the recovery of damaged supply chains and creating more livelihoods. As a global DT leader, Huawei is well positioned to play a key role in this transformation.” -Mohan Munasinghe, Nobel Peace Prize co-winner, and environment economist.

“The industry needs an operating system enabling ubiquitous interconnectivity for coal mines. For equipment, we need to continue improving and promoting dedicated operating systems such as Mine-Harmony to unify data access standards and specifications. Intelligent coal mining has been promoted rapidly in China. Digital technology is key to helping coal mines achieve this goal but still has a long way to go.” -Ge Shirong, President of China University of Mining and Technology and Beijing Academician of the Chinese Academy of Engineering