how could artificial intelligence be used in the coal mining industry

coal: a story of china

coal: a story of china

Start from the Pacific mouth of the Amur River just north of the China-Russian border. Follow the riveracross the national boundary as it becomes the Heilong Jiang, then strike west into the dense pine forests of the Khingan Mountains. Cross the patchy deserts that separate the yellow soils of Shaanxi province from the Mongolian steppe, completing your journey in the sandy plains of the Ordos Plateau.

Almost 200 million years ago, a colossal tectonic shift shook through this vast swath of land in northern China, ripping apart its once-thick plant coverage and replacing it with the varied terrain that characterizes the region today.

Changes beneath the surface have had far wider-reaching impact. New depression zones within the continental basin have cooked up vast reserves of brown lignite coal and black bituminous coal, the fuel that has fed Chinas surging economy for the past half-century.

China is responsible for over half of the worlds total consumption of coal. At peak times, nearly four-fifths of the countrys electricity comes from burning it. It is little wonder that in China coal has earned the sinister-sounding moniker black gold.

As this black gold has lured people and resources from around the country, a constellation of coal cities has gradually spread across the whole of Chinas northern areas. At the mercy of the health of the coal industry, these cities along with their inhabitants are now reeling from the effects of a severe, possibly terminal decline in the industry.

Slowing economic growth is stunting demand for coal, while at the same time China is beginning, slowly, to embrace clean energy alternatives. Yet as China turns its back on coal, the fates of some 4 million coal miners, their families, and the businesses that depend on them hang in the balance.

Chengcheng County lies in the middle of Shaanxi province, which, while squarely in the middle of China, is considered part of China's sprawling northwest. With its northern neighbor Inner Mongolia, eastern neighbor Shanxi, and Chinas northeasterly trio of Heilongjiang, Jilin, and Liaoning, Shaanxi is a crucial vertebra in Chinas coal-producing backbone. The local branch of Shaanxi provinces state mining group in Chengcheng County, the Chenghe Mining Bureau, has employed three generations of Liu Faweis family.

Lius father, who today lies paralyzed and bedridden, moved to the area in the early 1940s after selling the familys sole piglet for enough money to escape famine-ravaged Henan province. After over a decade of scraping by at a small, privately-run pit, he became one of the first group of miners to be awarded the stability and status of a position at a state-owned pit. Following the Communist Partys rise to power in 1949, the nationalization of industry heralded an unprecedented elevation in the status of the workers swept up in it.

Sweeping nationalization did not immediately translate to a surge in productivity, however. The civil war between the communists and nationalists had wreaked havoc on the countrys infrastructure. Damaged power plants were turning to burning soybeans for energy, while in the northeast, home to the most advanced mining technology and most skilled miners in the country at the time, trains were running on wood rather than on far more efficient coal.

The countrys first two Five-Year Plans (1953-1962) sought to repair and develop Chinas damaged heavy industry. In 1958, as China embarked on the Great Leap Forward a campaign of rapid industrial growth that is considered by many to have led to a famine that tore through parts of rural China from 1959 to 1961 production of coal grew by over 100 percent compared to the previous year. Although the industry was unable to sustain such growth for long, the spike in production nonetheless signaled that coal was set to become the backbone of Chinas industrial might.

With the launch in 1964 of the Third Front Movement, a campaign of massive industrial development of Chinas interior regions, geological survey teams from the resource-rich coal-producing regions of the northeastern provinces were sent westward to prospect for coal. As mines in Shaanxi developed at breakneck speed, hordes of agricultural workers gave up their work in the fields for a life in the pits, following the path that Lius father had taken decades before.

Zhao Wenxiangs late father was one of these workers. As Zhao, one of Liu Faweis colleagues at the Chenghe Mining Bureau, recalls, his father made the 180-kilometer journey to Chengcheng County from his village in late 1969 despite efforts by the local cadre to stop villagers from trading the simple and safe work of farming for the exhausting and hazardous work of mining.

The cadres warnings were well-founded. Cheap labor has remained a cornerstone of the mining industrys success, as reflected in the appalling conditions that workers have had to endure over the decades. Miners would descend into the darkness of the mines bare-chested, shovels slung across their shoulders, while coal dust hung around them in the stiflingly humid air. During long shifts down in the pits, miners not only have to endure fatigue, but also hunger.

Yet despite the harshness of their working environment, state-owned mines like those belonging to the Chenghe Mining Bureau flourished during the 1970s, as the government continued to pour money into their expansion. As the mines thrived, the credentials and pay slips of miners like Zhaos father drew the envy of those who had stayed behind in his village. His monthly salary of just over 100 yuan(then around $15) was more than enough to sustain him and his wife and three children back at home.

Mining areas like those belonging to the bureau were symbols of Chinas thundering industrial development, and they came to be ideal opportunities for the governments attempts to reclassify vast numbers of rural residents as urban citizens. By 1987, at the height of the campaign, Zhao, along with his siblings and his mother, followed his father out of the countryside and into the mining area. Mining areas, once isolated and void of any activity other than the clamor of machinery, gradually became independent, fully fledged communities, replete with schools, hospitals, and leisure facilities.

While they may have shared many of the same features and facilities of other urban centers around the country, these cities still revolved to a great extent around the matter that had borne them: coal. In 1987, Liu Fawei went to study at a technical school established by the Chenghe Mining Bureau to funnel further manpower into the local industry. After graduating, Liu joined the same mine as his father, though his duties as an electrician required more technical expertise than his fathers role as a low-level miner.

In the same year, then-19-year-old Zhao Wenxiang was recruited by one of the many mining companies that would sweep the campuses of high schools when graduation was around the corner. His initial excitement about following experienced miners underground soon gave way to mental and physical exhaustion.

In the 1990s, most of the work in pits around the country consisted of blast mining. Teams like Zhaos would spend over an hour descending to the extraction area, where they would shovel coal by hand on to a simple leather conveyor belt that took the extracted material up to the surface. Now 47, Zhao describes the feeling of working in those conditions as that of a bird with its wings clipped. The work was never-ending. However hard he tried, he would never be able to fly.

Data provided by the World Bank shows that, by 1995, annual production of electricity from coal had reached over 744 million megawatt-hours, almost double the amount just seven years before. As coal supply struggled to meet demand, the industry entered yet another period of state-led acceleration. Mines of all sizes shot up around the country. By the end of 1996, there were over 60,000 mines in operation nationally, of which nearly 90 percent were small-scale mines.

The scales had tipped too far. It was not too long before the government realized that the push for increased capacity had overshot its target. By 1998, China was facing a massive surplus in production. In order to cut capacity, the government began restructuring state-owned enterprises on a massive scale. The ministry for the coal industry was abolished, and management of key mines around the country was handed over to local governments.

Annual production plummeted in 2000 to an 11-year low, as over half the mines around the country closed, causing huge numbers of miners to lose their jobs. Of the 21.4 million people who lost their posts across all manner of industries between 1998 and 2000, more than a million were from state-owned coal enterprises.

Zhaos aging father was one of them. Following his layoff, he was diagnosed with liver cancer. In a matter of months, the illness took his life. To this day Zhao believes that his father died of grief, having been forced out of a job he had devoted himself to for decades.

By 2002, supply and demand were beginning to reach a new equilibrium, helped in part by China having joined the World Trade Organization the previous year. Encouraged by rises in annual profits of up to 80 percent in many state-owned mines, the Chinese government started to auction off mining rights, causing investors from the electricity, petroleum, and tobacco industries to clamor for a piece of the action.

After decades of turbulence, it finally seemed that Chinese coal had entered its golden age, and for miners around the country this meant a huge jump in wages. As a member of the transport team, Zhao did not enjoy the same remuneration as those on the front lines, but he could still expect to take home a comfortable 70,000-yuan (then approximately $8,500) wage package each year during the boom. By 2004, he traded in the bicycle hed ridden for years for his very own motorbike, and by 2009 he was the owner of a black 100,000-yuan Great Wall Motors sedan.

Even the financial crisis of 2008 did little to upset the industrys thunderous progress, thanks in part to huge injections of state capital. While the worlds other major economies suffered under the effects of the crash, the high-quality coal reserves of the northeast were enjoying unparalleled productivity. At the state-owned Heilongjiang Longmay Mining Group, the largest coal firm in the whole of the three northeastern provinces, the price for high-grade coking coal shot up from 600 yuan per ton in 2005 to 2,000 yuan per ton in 2008.

During these golden years, the Chenghe Mining Bureau increased investment in the facilities for miners families living in Chengcheng County. Liu Faweis and Zhao Wenxiangs families were both given new apartments in the Sunshine Place housing complex, which featured its very own kindergarten. Just next door to them sat a well-equipped hospital built by none other than the mining bureau itself.

The apparent benefits that coal was bringing not only to miners wallets but also to their quality of living were enough to guarantee a steady flow of fresh talent into the pits. When Liu Faweis son Liu Pingan graduated from the Chenghe Mining Bureaus school of technology, national coal prices had just hit an all-time high. It was 2011, and one ton of steam coal was fetching 860 yuan on average. The beginning of Liu Pingans career in the mines albeit as a low-ranking member of the security staff was looking even rosier than that of his father or grandfather.

A sustained depression in the coal market has taken hold following the gradual slowing of Chinas economic growth. By the end of 2015, more than 90 percent of Chinas coal enterprises were incurring losses. Mines in the northeast, bursting at the seams with miners following the glorious boom of the 2000s, were suddenly faced with massive overhead and dwindling revenue. In 2015, following the previous years losses of nearly 6 billion yuan, Longmay launched the first phase of a staff transfer plan, in the hope of pulling the company out of its predicament by reducing labor costs.

One of the workers facing the prospect of transferal is Zhao Duo, a soft-spoken 24-year-old who works at a Longmay-owned mine in Qitaihe, a coal city that sits in the beak of the chicken that China's appearance on a map is often likened to.

Zhao joined the mine as one of the last groups of miners to be funneled into Longmay after graduating in 2014 from a mining course at the Heilongjiang University of Science and Technology in the provinces capital, Harbin. Memories of the dining table overflowing with sumptuous food in the years leading up to 2012 the literal fruits of his fathers then-healthy salary were soon replaced by the sobering reality of cuts in wages and the possibility of forced transferals. Zhao does not complain, however. Through a persistent smile, he says that he will stay on in Qitaihe until his position becomes untenable. Everything he has is there.

Other miners have taken a more proactive approach, looking for part-time work to supplement their dwindling salaries and provide a back-up should they lose their jobs completely. Eighty kilometers south of Qitaihe is Jixi, another of Heilongjiangs great coal cities. In deep winter, the temperature drops to 20 degrees below zero, yet crowds of part-time cab drivers line the streets, waiting for prospective passengers looking to make the journey out of town to the nearby coal pits for a days work.

One of the drivers is Yin Fuqiang, a 48-year-old worker at the Jixi Mining Bureau. A month into 2016 and the mine has yet to pay out wages owed to workers from the previous year, leaving Yin with no choice but to work as a cab driver in his spare time to supplement his familys income.

After the bridge of his nose was broken by a collapsed roof-beam in the mines, Yin was transferred away from frontline work to an administrative position. Though decades in the pits have left his lungs riddled with miscellaneous chronic ailments, Yin's hand is never without a cigarette while he is driving. For him, smoking is an indispensable means of keeping stress and resentment at bay.

Like Zhao Duo, Yin Fuqiang has refused to sign up for the staff transferal that his mine had been pushing for. Though a transfer might equate to a form of promotion, he is unwilling to abandon the skills he has amassed over the years and follow hundreds of thousands of other miners into unrelated sectors like afforestation, land reclamation, and agriculture. Despite the damage that the industry has done to his body and the difficulties that delayed wages have brought on his family, Yin remains loyal to coal.

But not all miners are content to keep their heads low and weather the storm. Delays in the payment of wages at state-owned mines have been sparking protests in many mining communities around the northeast from as early as July 2015.

The most recent spate of worker action took place in March 2016 in Shuangyashan, Heilongjiang, when workers gathered around the Longmay Groups headquarters to protest wage cuts and delays. Images of banners scrawled with messages like We must live, we must eat soon made the rounds on social media platforms like microblogging site Weibo.

Exposure of miners discontent may have been concentrated in the northeastern mining communities, but the stalling of the industry and the tension this has caused between mines and miners are being felt across all of Chinas coal-producing regions. In 2015, when 37 of Chinas publicly traded coal companies released their third-quarter earnings reports, Shaanxis coal firms led the list of those with the heaviest losses. In one quarter alone, firms across the province suffered a collective negative profit of over 1.8 billion yuan.

It took Liu Fawei in Chengcheng County six whole months to receive his wages from June 2015. In the months that he was not receiving any income from the mine at all, Liu did not miss a day of work, concerned that any transgression would jeopardize his job and, consequently, the well-being of his family.

Hi son Liu Pingan was unable to realize the hopes he had at graduation for a stable and well-paid career in the mines. Now 29, and married with twin boys, he doesnt share his fathers patience. In October 2015, he made the 900-kilometer journey to Chengdu, capital of the southwestern province of Sichuan. Like many young miners, he was leaving stagnating industry behind to find work in a city with a more diverse economy. Yet with such narrow qualifications and work experience, Liu could only find work doing odd jobs for a shoe vendor. The money barely covered his own rent and meals, and it certainly didnt leave him with anything to send back to his family.

Several months later, Liu Pingan has succumbed to the calls of his parents to move back into the family home with his wife and sons and give the pits another try. Though Liu may be making a fraction more than he did in Chengdu, his and his fathers mining salaries are barely enough to sustain the most basic needs of the household. The tiny two-bedroom apartment now houses eight people: Liu with his wife and two sons, his young sister who has not yet left school, his parents, and his bedridden grandfather.

The mining industry pulled the Lius out of poverty, and the older members of the family are too loyal to give up on it, despite the insufficiency and delays of the wages. For those like Liu willing to explore the world outside the mines, they have struggled to find work where they can apply their limited expertise.

Following a June 2015 pledge by the State Administration of Work Safety to tackle issues of safety and conflict between high labor costs and dwindling productivity, some state-run mining firms are looking to automatize the mining process.

Against the backdrop of plummeting coal prices around the country, the Hongliulin mine in Shenmu County, 500 kilometers north of Chengcheng County, managed to turn a profit in the year 2015, according to the mines head of publicity Wang Zejun. Using fully mechanized extraction, the small-scale mine produced more coal last year than all the mines affiliated with the Chenghe Mining Bureau, despite employing less than a tenth of the staff.

The advanced mining equipment used at the mine is imported from the U.S. and Germany, and it has increased demands on the technical qualifications of the miners. Small, young, and highly qualified, the workforce in such mines strikes a hard contrast with that of the majority of mines, which have relied on the traditional labor-intensive model.

Aside from the attack on human labor that the policy of mechanization represents, industry observers also predict that China is entering an era of de-carbonization. While market forces were the principal instigators of previous fluctuations in the industry, a sinister shadow hitherto largely absent in political dialogue is looming over the current decline: pollution.

Burning coal produces carbon dioxide, nitrogen oxides, and harmful particulate matter small enough to enter the lungs, and it is widely regarded as the key polluting factor in smog formation. The smog that lays siege to Beijing and its surrounding provincial cities is causing rising anguish among residents, as the severity of the health risk that such smog poses has become more apparent in recent years.

In both Shaanxi and the northeast, solar plants and wind farms have already begun to dot the landscape. Towering turbines stand on the ground that covers, hundreds of meters below, the emptying shells of pit mines that once teemed with activity.

Chinas pledge at the Paris Climate Change Conference in November 2015 suggests that saying a final farewell to coal remains a real possibility. According to statistics released by the National Energy Administration, in 2015 the countrys total grid capacity for wind and solar energy reached 186 million and 40 million megawatt-hours respectively, increases of 21 percent and 57 percent on the previous year. In February 2016, the government announced that in the coming three to five years, there will be a total reduction in coal production of 1 billion tons, through both cutbacks in capacity and a further series of restructuring. The position of coal-fired power plants, for so long the primary generators of energy in China, is being gradually weakened by renewable forms of energy.

Though in decline, the mining industry continues to make its mark on the land and its people. A March report released by Greenpeace found that although coal production has been in decline since 2014, ongoing mining activity across China is draining drought-prone areas of water on a colossal scale.

Despite reforms in safety regulation, Chinas mines remain the most dangerous in the world. Accidents with dozens of fatalities appear in headlines almost monthly, with the most recent being a late-night incident that caused the deaths of 19 miners at an underground mine in northern Shanxi province.

Yet despite the human tragedies, the environmental cost, the unpaid wages, the strikes and protests, the individuals and families who have built their lives around the mines are reluctant to give up hope on the prospect of a return to the heady days of coals golden age.

emerging automation in the coal mining industry you need to know about

emerging automation in the coal mining industry you need to know about

Coal mining has always been a time and labor intensive process. Add to it the processes of refining and processing of coal, and you have a highly energy draining process at your hands that requires way too much capital and way too many workers. Over the past several years, many innovations have led the way for top notch machineries that have allowed the coal mining industry to breathe an air of respite. This has solely been credited to hands-on research and development of advanced technologies.

Gone are the days when miners used pickaxes, oil lanterns, and other hand held tools to go underground and mine manually for days at a stretch. In fact, most coal mines dont even require workers to go deep under the ground. Thanks to the sophisticated automation solutions that are used to plan and design mining fields, blast sites, and more. Here, automated machineries and vehicles are sent to carry out the process of mining in lesser time.

The coal mining industry operates in a way such that it has and continues to put a lot of pressure on the environment. It has utilized vast resources of energy, water, machineries, human labor, and more, and many a times, it has uprooted tribal settlements near the mining area, making them homeless. The tremendous social, economic, and environmental pressure exerted by the coal mining industry over the past several decades has forced it to change the way it operates and approach mining with a much more safe and sustainable way.

With time, the advanced technologies have also paved the path for automated technologies that have further helped the industry to reduce the need for a large workforce and a huge capital. The main idea of introducing automations in the coal mining process was to primarily eliminate the need for human labor and increase productivity. This has ultimately led to faster and more efficient mining processes.

Its important to note that, in developing countries, where the cost of labor is very low, the introduction of mining automations only serves the purpose of eliminating the need for human labor and increasing productivity and doesnt help to reduce the amount of investments made. This is because the incentives earned for increased productivity and efficiency are quite minimal. Automations in the coal mining industry can be applied to two major areas:

These automations have started making a place for themselves in the industry; however, they are still in their transition phase. Its still a long way to go for the entire coal mining process to become completely automated. Read on to understand what have been the recent emerging automations in the coal mining industry.

The terrain where coal mining takes place is incredibly rough and risky. In addition, you need a lot of heavy machinery to navigate through the terrain well and carry out mining operations seamlessly. This requires drivers of bulldozers, excavators, and other heavy machinery to be extra careful. They need to be trained well to be able to drive on such rough terrains, where a single mishandling could lead to damage to property and loss of lives. Advanced technology has allowed such heavy machineries to be equipped with driver assist automations just like the ones we have in our cars.

The spotting assist feature allows the mining machine drivers to avoid any obstacle in their path. In addition, the collision avoidance systems alert the driver about the proximity of obstacles, such as boulders and sharp objects. Putting the machine in reverse and moving back and forth on bad trails have been made very easy with such driver assist features. Currently, some machines also provide driving assistance features that allow the drivers to take care of things in their blind spots.

Remote control automations take it a whole step further by allowing mining machine drivers to control the machinery from a distance with the help of a remote control device. They can stand in the line of sight of the complete landscape and control numerous pieces of mining equipment, such as excavators, large drills, bulldozers, loaders, dumpers, graders, and rollers, from a remote location. While these remote control automations allow the drivers to control the operations of the mining equipment from a distance, it reduces the productivity. This is because it can get difficult to handle the equipment from such a long distance without getting the feel of what you are driving around.

However, the main application of remote control automations is in scenarios where the situation is incredibly dangerous for people to go in, such as fallen debris, unstable or sinking terrain, high risk areas, and underground mining.

This allows miners and engineers to carry on with their regular operations even in high risk areas. They dont have to lose out on abundant reserves and deposits of coal simply because they are facing risks to machinery and human lives. In short, miners, engineers, and machinery handlers can now stand away from the risky areas and still dig to get out to coal reserves. To add on, these controlled automated mining machineries are pretty affordable.

Going another step further, we have teleoperated mining equipment. Miners and engineers can now choose automated machineries that allow them to carry out the mining operations while being miles away from the actual site of mining. Cameras, sensors, positioning devices and software, mirrors, and more are used to view the entire area that needs mining. Controlling devices for these equipment include joysticks, hand held controls, and more. Research is also ongoing about how these mining operations can be carried out by using remote devices, such as desktops, where a particular action can be triggered with a single touch on the screen.

Teleoperated mining automations offer a better vantage point and control than those offered by remote control automations. Since positioning devices and software are used, the handling of things gets much easier; however, it does take a little more time to get better results. These automations are highly useful when you need to dig underground in extremely confined areas, where the entry of humans can be a huge risk to their lives.

By fully automating the mining equipment, the human laborers can be replaced with robots. Robotics and artificial intelligence can be incorporated into the vehicles and machineries, enabling them to start the engine, steer the vehicle or machine, accelerate, slow down, apply brakes, drill through the surface, mine for coal, and more, all on their own without any remote assistance.

These vehicles or machines can also carry out very specific jobs, such as blade control and dump bed control. Although these are much costlier to procure, they offer a huge boost to productivity since human control is eliminated. In addition, there is absolutely no need to be behind the controls all the time tracking and triggering every little move and shift. It is, however, important to note that, even though fully automated vehicles and machines can eliminate the need for numerous labor workers, you would still need to hire mining facilitators and troubleshooting experts, who can deal with any technical errors that come up in the machine or vehicle.

A coal mining field is an incredibly dangerous and a risky place to be at. You need to be on your toes every second and have to make sure that you arent digging in high risk areas, where the ground underneath can cave in or sink. If it were to happen, it can lead to not just a waste of effort, resources, and capital, but also the loss of many lives of the miners working in the field. Mining software has helped to automate the process of designing layouts and putting vertical lifts, and blasts in appropriate locations.

It uses technology to automatically detect the stress levels in the numerous layers of the ground, thus allowing you to set up planned and strategic locations. The loss of effort, resources, capital, and human lives can therefore be reduced to a minimum, and you do not have to spend a lot of time figuring out where you can install a particular thing.

There are several structures that need to be installed when you conduct mining. These include longwall pillars, multiple seams, roof bolt systems, retreat mining pillars, and more. The stability and strength of these structures are of paramount importance, and no part of their design or layout can be overlooked or compromised with. There have been numerous previous cases where people have lost their lives or have had to deal with severe injuries and even permanent damages such as paralysis at times when one of these structures gave away or wasnt stable enough to sustain.

Automation solutions have allowed miners and engineers to have faith in such structures since the software can automatically analyse the stability of these structures. If they are unstable, the software will prompt a warning asking you to make necessary changes to sustain the structures. These solutions are low cost and quite affordable. They are also incredibly easy to use and can provide quick results, thus reducing the tremendous amount of time, which was previously spent on manually checking the strength and stability of the structure.

Large datasets have to be evaluated at high speed to prove the economic viability of the structures. In addition, these structures are incredibly expensive to install. A longwall pillar could take anywhere from $60 million dollars and more to install. Even the slightest issue could cause the loss of a truckload of money. Once the geological area is assessed, the software can provide 3D models for the structural interpretation.

Not all mining is done underground, and the layout designs for surface mining can be obtained using automation solutions as well. These software dont just recommend layout plans, but also test them in plan, section, and 3D views. This allows them to make sure that all the corners are covered and no high risk areas are being overlooked when preparing the design. This automation in geological and surface coal mining has allowed miners and engineers to navigate through some extremely difficult terrains with a lot of ease.

This automation tool examines the extent of deposits in the ground and calculates how much ore can be mined. A geological model is analysed, which then provides information on mineable and non-mineable coal deposits in the area. In this way, miners and engineers no longer have to keep digging in a place for months and end up with very little to no ores.

The next comes a scheduling model, which examines the sustainability of the digging patterns suggested by the engineering model. It also determines the rate and quantity of digging or mining required. This is a smart tool that takes care of all high stress points that are currently present on the ground or likely to develop in the near future. It also provides recommendations on altering the current parameters to continue a steady stream of mining in a particular area. This allows miners and engineers to make sure that there are no gaps in the plan ahead and the operations arent affected too much.

One obvious and the most important advantage of automations in the coal mining industry is improved and better safety of all workers involved in every process. They no longer have to take a huge risk on their lives when going underground for mining. Much more stable and strong structures, which have undergone thorough testing before being put up in the location, are built. Moreover, remote and teleoperated machines allow miners and engineers to get the desired amount of coal they want without being in close proximity to the mines or caves. Thus, even if there is an unforeseen and sudden accident where the mine caves in or sinks or a structure falls down no lives will be harmed.

Numerous previous mining projects that were undertaken yielded not so great results, but they sure utilized loads of environmental resources, such as energy, water, and wood. This has and continues to impact the environment heavily. Thus, social and governmental regulations began to be introduced to make sure that mining companies werent exploiting the environmental resources. This led to the depletion of throughput in mining companies since they didnt have the required tools and technologies to use resources sustainably.

Mining is an incredibly energy draining job, especially for drivers. With loads of automation coming into play with respect to the drills and vehicles, drivers can take a breath of respite and relax. Drivers no longer have to navigate through rough terrains without being aware of what they might have to tackle next. They are highly informed about what lies ahead, and they can easily drive without putting too much effort or worrying about the statistics of things.

Now that numerous mining operations can be taken care of without having to be in close proximity to the coal caves and deposits, especially underground mines, working conditions have improved incredibly. Most processes and operations are carried out from a distance, thus reducing the chances of health ailments such as asthma and bronchitis to a minimum. Workers are also safe from physical harm, such as fractures, wounds, or even permanent damage such as paralysis. Automation of numerous processes has reduced the chances of deaths in coal mines by a large extent.

Sophisticated automation tools are incredibly good at what they do and rarely fail. They also alert engineers when a system or machine is about to go bust and needs immediate maintenance. Previously, there used to be loads of occurrences of unscheduled maintenance since engineers had no idea what was working and what wasnt. With such sophisticated machinery and processes, the occurrences of unscheduled maintenance have reduced a lot. This is because these tools allow the scheduled work to be carried on as usual without any unforeseen delays or hindrances.

All machines, drills, and vehicles in a coal mine operate on either fuel or energy. When operations and processes are well scheduled, planned, tried, and tested, fuel and energy are used in a highly practical and an efficient manner. There is no wastage of fuel and energy on processes that are later deemed useless or redundant. This allows better resource maintenance without impacting the environment much.

The biggest drawback of introducing automations in the coal mining industry is the loss of numerous jobs. Miners are usually workers from marginalized or underprivileged communities who do not have any other job opportunities available to them. When automated tools take their places, they have nowhere to get livelihood from. Another problem is that, even though a lot of research is going on regarding these automations, there arent enough stakeholders who are willing to test out things in real coal mines.

future of ai: 7 ways artificial intelligence will change the world | built in

future of ai: 7 ways artificial intelligence will change the world | built in

In a nondescript building close to downtown Chicago, Marc Gyongyosi and the small but growing crew of IFM/Onetrack.AI have one rule that rules them all: think simple. The words are written in simple font on a simple sheet of paper thats stuck to a rear upstairs wall of their industrial two-story workspace. What theyre doing here with artificial intelligence, however, isnt simple at all.

Sitting at his cluttered desk, located near an oft-used ping-pong table and prototypes of drones from his college days suspended overhead, Gyongyosi punches some keys on a laptop to pull up grainy video footage of a forklift driver operating his vehicle in a warehouse. It was captured from overhead courtesy of a Onetrack.AI forklift vision system.

Employing machine learning and computer vision for detection and classification of various safety events, the shoebox-sized device doesnt see all, but it sees plenty. Like which way the driver is looking as he operates the vehicle, how fast hes driving, where hes driving, locations of the people around him and how other forklift operators are maneuvering their vehicles. IFMs software automatically detects safety violations (for example, cell phone use) and notifies warehouse managers so they can take immediate action. The main goals are to prevent accidents and increase efficiency. The mere knowledge that one of IFMs devices is watching, Gyongyosi claims, has had a huge effect.

If you think about a camera, it really is the richest sensor available to us today at a very interesting price point, he says. Because of smartphones, camera and image sensors have become incredibly inexpensive, yet we capture a lot of information. From an image, we might be able to infer 25 signals today, but six months from now well be able to infer 100 or 150 signals from that same image. The only difference is the software thats looking at the image. And thats why this is so compelling, because we can offer a very important core feature set today, but then over time all our systems are learning from each other. Every customer is able to benefit from every other customer that we bring on board because our systems start to see and learn more processes and detect more things that are important and relevant.

IFM is just one of countless AI innovators in a field thats hotter than ever and getting more so all the time. Heres a good indicator: Of the 9,100 patents received by IBM inventors in 2018, 1,600 (or nearly 18 percent) were AI-related. Heres another: Tesla founder and tech titan Elon Musk recently donated $10 million to fund ongoing research at the non-profit research company OpenAI a mere drop in the proverbial bucket if his $1 billion co-pledge in 2015 is any indication. And in 2017, Russian president Vladimir Putin told school children that Whoever becomes the leader in this sphere [AI] will become the ruler of the world. He then tossed his head back and laughed maniacally.

OK, that last thing is false. This, however, is not: After more than seven decades marked by hoopla and sporadic dormancy during a multi-wave evolutionary period that began with so-called knowledge engineering, progressed to model- and algorithm-based machine learning and is increasingly focused on perception, reasoning and generalization, AI has re-taken center stage as never before. And it wont cede the spotlight anytime soon.

Theres virtually no major industry modern AI more specifically, narrow AI, which performs objective functions using data-trained models and often falls into the categories of deep learning or machine learning hasnt already affected. Thats especially true in the past few years, as data collection and analysis has ramped up considerably thanks to robust IoT connectivity, the proliferation of connected devices and ever-speedier computer processing.

Some sectors are at the start of their AI journey, others are veteran travelers. Both have a long way to go. Regardless, the impact artificial intelligence is having on our present day lives is hard to ignore:

I think anybody making assumptions about the capabilities of intelligent software capping out at some point are mistaken, says David Vandegrift, CTO and co-founder of the customer relationship management firm 4Degrees.

With companies spending nearly $20 billion collective dollars on AI products and services annually, tech giants like Google, Apple, Microsoft and Amazon spending billions to create those products and services, universities making AI a more prominent part of their respective curricula (MIT alone is dropping $1 billion on a new college devoted solely to computing, with an AI focus), and the U.S. Department of Defense upping its AI game, big things are bound to happen. Some of those developments are well on their way to being fully realized; some are merely theoretical and might remain so. All are disruptive, for better and potentially worse, and theres no downturn in sight.

Lots of industries go through this pattern of winter, winter, and then an eternal spring, former Google Brain leader and Baidu chief scientist Andrew Ng told ZDNet late last year. We may be in the eternal spring of AI.

During a lecture last fall at Northwestern University, AI guru Kai-Fu Lee championed AI technology and its forthcoming impact while also noting its side effects and limitations. Of the former, he warned:

The bottom 90 percent, especially the bottom 50 percent of the world in terms of income or education, will be badly hurt with job displacementThe simple question to ask is, How routine is a job? And that is how likely [it is] a job will be replaced by AI, because AI can, within the routine task, learn to optimize itself. And the more quantitative, the more objective the job isseparating things into bins, washing dishes, picking fruits and answering customer service callsthose are very much scripted tasks that are repetitive and routine in nature. In the matter of five, 10 or 15 years, they will be displaced by AI.

Lees opinion was recently echoed by Infosys president Mohit Joshi, who at this years Davos gathering told the New York Times, People are looking to achieve very big numbers. Earlier they had incremental, 5 to 10 percent goals in reducing their workforce. Now theyre saying, Why cant we do it with 1 percent of the people we have?

On a more upbeat note, Lee stressed that todays AI is useless in two significant ways: it has no creativity and no capacity for compassion or love. Rather, its a tool to amplify human creativity. His solution? Those with jobs that involve repetitive or routine tasks must learn new skills so as not to be left by the wayside. Amazon even offers its employees money to train for jobs at other companies.

One of the absolute prerequisites for AI to be successful in many [areas] is that we invest tremendously in education to retrain people for new jobs, says Klara Nahrstedt, a computer science professor at the University of Illinois at UrbanaChampaign and director of the schools Coordinated Science Laboratory.

People need to learn about programming like they learn a new language, he says, and they need to do that as early as possible because it really is the future. In the future, if you dont know coding, you dont know programming, its only going to get more difficult.

And while many of those who are forced out of jobs by technology will find new ones, Vandegrift says, that wont happen overnight. As with Americas transition from an agricultural to an industrial economy during the Industrial Revolution, which played a big role in causing the Great Depression, people eventually got back on their feet. The short-term impact, however, was massive.

Mike Mendelson, a learner experience designer for NVIDIA, is a different kind of educator than Nahrstedt. He works with developers who want to learn more about AI and apply that knowledge to their businesses.

If they understand what the technology is capable of and they understand the domain very well, they start to make connections and say, Maybe this is an AI problem, maybe thats an AI problem, he says. Thats more often the case than I have a specific problem I want to solve.

In Mendelsons view, some of the most intriguing AI research and experimentation that will have near-future ramifications is happening in two areas: reinforcement learning, which deals in rewards and punishment rather than labeled data; and generative adversarial networks (GAN for short) that allow computer algorithms to create rather than merely assess by pitting two nets against each other. The former is exemplified by the Go-playing prowess of Google DeepMinds Alpha Go Zero, the latter by original image or audio generation thats based on learning about a certain subject like celebrities or a particular type of music.

On a far grander scale, AI is poised to have a major effect on sustainability, climate change and environmental issues. Ideally and partly through the use of sophisticated sensors, cities will become less congested, less polluted and generally more livable. Inroads are already being made.

Once you predict something, you can prescribe certain policies and rules, Nahrstedt says. Such as sensors on cars that send data about traffic conditions could predict potential problems and optimize the flow of cars. This is not yet perfected by any means, she says. Its just in its infancy. But years down the road, it will play a really big role.

Of course, much has been made of the fact that AIs reliance on big data is already impacting privacy in a major way. Look no further than Cambridge Analyticas Facebook shenanigans or Amazons Alexa eavesdropping, two among many examples of tech gone wild. Without proper regulations and self-imposed limitations, critics argue, the situation will get even worse. In 2015, Apple CEO Tim Cook derided competitors Google and Facebook (surprise!) for greed-driven data mining.

Advancing AI by collecting huge personal profiles is laziness, not efficiency," he said. For artificial intelligence to be truly smart, it must respect human values, including privacy. If we get this wrong, the dangers are profound."

If implemented responsibly, AI can benefit society. However, as is the case with most emerging technology, there is a real risk that commercial and state use has a detrimental impact on human rights."

Plenty of others agree. In a paper published recently by UK-based human rights and privacy groups Article 19 and Privacy International, anxiety about AI is reserved for its everyday functions rather than a cataclysmic shift like the advent of robot overlords.

If implemented responsibly, AI can benefit society, the authors write. However, as is the case with most emerging technology, there is a real risk that commercial and state use has a detrimental impact on human rights. In particular, applications of these technologies frequently rely on the generation, collection, processing, and sharing of large amounts of data, both about individual and collective behavior. This data can be used to profile individuals and predict future behavior. While some of these uses, like spam filters or suggested items for online shopping, may seem benign, others can have more serious repercussions and may even pose unprecedented threats to the right to privacy and the right to freedom of expression and information (freedom of expression). The use of AI can also impact the exercise of a number of other rights, including the right to an effective remedy, the right to a fair trial, and the right to freedom from discrimination.

Speaking at Londons Westminster Abbey in late November of 2018, internationally renowned AI expert Stuart Russell joked (or not) about his formal agreement with journalists that I wont talk to them unless they agree not to put a Terminator robot in the article. His quip revealed an obvious contempt for Hollywood representations of far-future AI, which tend toward the overwrought and apocalyptic. What Russell referred to as human-level AI, also known as artificial general intelligence, has long been fodder for fantasy. But the chances of its being realized anytime soon, or at all, are pretty slim. The machines almost certainly wont rise (sorry, Dr. Russell) during the lifetime of anyone reading this story.

There are still major breakthroughs that have to happen before we reach anything that resembles human-level AI, Russell explained. One example is the ability to really understand the content of language so we can translate between languages using machines When humans do machine translation, they understand the content and then express it. And right now machines are not very good at understanding the content of language. If that goal is reached, we would have systems that could then read and understand everything the human race has ever written, and this is something that a human being can't do... Once we have that capability, you could then query all of human knowledge and it would be able to synthesize and integrate and answer questions that no human being has ever been able to answer because they haven't read and been able to put together and join the dots between things that have remained separate throughout history.

Thats a mouthful. And a mind full. On the subject of which, emulating the human brain is exceedingly difficult and yet another reason for AGIs still-hypothetical future. Longtime University of Michigan engineering and computer science professor John Laird has conducted research in the field for several decades.

The goal has always been to try to build what we call the cognitive architecture, what we think is innate to an intelligence system, he says of work thats largely inspired by human psychology. One of the things we know, for example, is the human brain is not really just a homogenous set of neurons. Theres a real structure in terms of different components, some of which are associated with knowledge about how to do things in the world.

Thats called procedural memory. Then theres knowledge based on general facts, a.k.a. semantic memory, as well as knowledge about previous experiences (or personal facts) thats called episodic memory. One of the projects at Lairds lab involves using natural language instructions to teach a robot simple games like Tic-Tac-Toe and puzzles. Those instructions typically involve a description of the goal, a rundown of legal moves and failure situations. The robot internalizes those directives and uses them to plan its actions. As ever, though, breakthroughs are slow to come slower, anyway, than Laird and his fellow researchers would like.

More than a few leading AI figures subscribe (some more hyperbolically than others) to a nightmare scenario that involves whats known as singularity, whereby superintelligent machines take over and permanently alter human existence through enslavement or eradication.

The late theoretical physicist Stephen Hawking famously postulated that if AI itself begins designing better AI than human programmers, the result could be machines whose intelligence exceeds ours by more than ours exceeds that of snails. Elon Musk believes and has for years warned that AGI is humanitys biggest existential threat. Efforts to bring it about, he has said, are like summoning the demon. He has even expressed concern that his pal, Google co-founder and Alphabet CEO Larry Page, could accidentally shepherd something evil into existence despite his best intentions. Say, for example, a fleet of artificial intelligence-enhanced robots capable of destroying mankind. (Musk, you might know, has a flair for the dramatic.) Even IFMs Gyongyosi, no alarmist when it comes to AI predictions, rules nothing out. At some point, he says, humans will no longer need to train systems; theyll learn and evolve on their own.

I dont think the methods we use currently in these areas will lead to machines that decide to kill us, he says. I think that maybe five or ten years from now, Ill have to reevaluate that statement because well have different methods available and different ways to go about these things.

Last spring, Oxford Universitys Future of Humanity Institute published the results of an AI survey. Titled When Will AI Exceed Human Performance? Evidence from AI Experts, it contains estimates from 352 machine learning researchers about AIs evolution in years to come. There were lots of optimists in this group. By 2026, a median number of respondents said, machines will be capable of writing school essays; by 2027 self-driving trucks will render drivers unnecessary; by 2031 AI will outperform humans in the retail sector; by 2049 AI could be the next Stephen King and by 2053 the next Charlie Teo. The slightly jarring capper: by 2137, all human jobs will be automated. But what of humans themselves? Sipping umbrella drinks served by droids, no doubt.

Currently, computers can handle a little more than 10,000 words, he explains. So, a few million neurons. But human brains have billions of neurons that are connected in a very intriguing and complex way, and the current state-of-the-art [technology] is just straightforward connections following very easy patterns. So going from a few million neurons to billions of neurons with current hardware and software technologies I don't see that happening.

Klabjan also puts little stockin extreme scenarios the type involving, say, murderous cyborgs that turn the earth into asmoldering hellscape. Hes much more concerned with machines war robots, for instance being fed faulty incentives by nefarious humans. As MIT physics professors and leading AI researcher Max Tegmark put it in a 2018 TED Talk, The real threat from AI isnt malice, like in silly Hollywood movies, but competence AI accomplishing goals that just arent aligned with ours. Thats Lairds take, too.

What Laird worries most about isnt evil AI, per se, but evil humans using AI as a sort of false force multiplier for things like bank robbery and credit card fraud, among many other crimes. And so, while hes often frustrated with the pace of progress, AIs slow burn may actually be a blessing.

There are several major breakthroughs that have to occur, and those could come very quickly, Russell said during his Westminster talk. Referencing the rapid transformational effect of nuclear fission (atom splitting) by British physicist Ernest Rutherford in 1917, he added, Its very, very hard to predict when these conceptual breakthroughs are going to happen.

But whenever they do, if they do, he emphasized the importance of preparation. That means starting or continuing discussions about the ethical use of A.G.I. and whether it should be regulated. That means working to eliminate data bias, which has a corrupting effect on algorithms and is currently a fat fly in the AI ointment. That means working to invent and augment security measures capable of keeping the technology in check. And it means having the humility to realize that just because we can doesnt mean we should.

Our situation with technology is complicated, but the big picture is rather simple, Tegmark said during his TED Talk. Most AGI researchers expect AGI within decades, and if we just bumble into this unprepared, it will probably be the biggest mistake in human history. It could enable brutal global dictatorship with unprecedented inequality, surveillance, suffering and maybe even human extinction. But if we steer carefully, we could end up in a fantastic future where everybodys better offthe poor are richer, the rich are richer, everybodys healthy and free to live out their dreams.

intelligent and ecological coal mining as well as clean utilization technology in china: review and prospects - sciencedirect

intelligent and ecological coal mining as well as clean utilization technology in china: review and prospects - sciencedirect

Coal is an essential fossil fuel in China; however, coal mining and its utilization are being under the increasing pressure from ecological and environmental protection. Therefore, the consulting project Technical Revolution in Ecological and Efficient Coal Mining and Utilization & Intelligence and Diverse Coordination of Coal-based Energy System, initiated by Chinese Academy of Engineering, puts forward three stages (3.0, 4.0 and 5.0) of Chinas coal industry development strategy. Aimed at reduced staff, ultra-low ecological damage, and emission level near to natural gas, breakthroughs should be achieved in the following three key technologies during the China Coal Industry 3.0 stage (20162025): including intelligent coal mining, ecological mining, ultra-low emission and environmental protection. This paper focuses on the development trends of the China Coal Industry 3.0 and its support for China Coal Industry 4.0 and 5.0 is analyzed and prospected as well, which may offer technical assistance and strategy orientation for realizing the transformation from traditional coal energy to clean energy.

coal miners could 'wear suits and ties at work', says huawei chief

coal miners could 'wear suits and ties at work', says huawei chief

Huawei CEO Ren Zhengfei, speaking at the opening of the companys Intelligent Mining Innovation Lab in Chinas Shanxi province, discussed how the main goal of 5G is enabling the digital transformation of vertical industries, including transportation hubs, ports, mines and manufacturing. The point of facilities such as the Intelligent Mining Innovation Lab is to learn more about the needs of these industries, Zhengfei said.

Last year Huawei started working with a mining equipment manufacturer, Yuexin Zhineng, to continue developing autonomous mining equipment with some autonomous assets already in use at a molybdenum mine in Henan province. Having collaborated prior to the 5G era on similar projects, Huawei and Yuexin Zhineng are now bringing 5G into the mix with numerous base stations deployed at a mining facility last year in support of autonomous equipment testing.

At the lab in Shanxi, more than 220 staff members from both Huawei and various coal mining interests, work on what Zhengfei called a co-leadership mechanism, where leaders from the coal industry have a greater say on mining aspects, while Huawei leaders have a greater say on the electronics side of things.

Zhengfei noted that while different verticals need different things from 5G, most of the technologies are the same. Our main goal is to increase the adoption of electronic, software and computing systems in different industries.

Specific to mining, he mentioned using ICT to improve worker safety and increase worker efficiency. Autonomous equipment and operations will ultimately reduce staffing needs with an emphasis on getting workers out of mines to the extent possible. We can also enable coal mine workers to wear suits and ties at work, and propel the mining machinery industryforward.

In a conversation with Enterprise IoT Insights, Huawei Carrier Business Group CTO Paul Scanlan discussed how 5G would be delivered to vertical industrieswill public networks stand up to the needs of enterprise, will private network deployments win out, or is a hybrid approach more likely? Its about the DNA of the operator and how they engage in the discussion, he said. There are operators that commit teams of people to solutions.

In terms of the long-term revenue opportunity carriers can tap into by properly developing and selling vertical-specific 5G solutions, A port doesnt churn, Scanlan said. A robot doesnt churn. A water meter doesnt churn. I wouldve thought the operators would understand that. Its very close relationshipyoure providing a significant amount of value. Its a very high network worth-type customer.

Editor in Chief [email protected] Sean focuses on multiple subject areas including 5G, Open RAN, hybrid cloud, edge computing, and Industry 4.0. He also hosts Arden Media's podcast Will 5G Change the World? Prior to his work at Arden Media, Sean studied journalism and literature at the University of Mississippi then spent six years based in Key West, Florida, working as a reporter for the Miami Herald Media Company. He currently lives in Fayetteville, Arkansas.

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