Artificial intelligence is finding more applications in different industries, and mining is one of them. South Africa, Africa's top mining country, is leading the way in AI and IoT usage in resource extraction on the continent.
Artificial Intelligence (AI) has emerged in recent times as a revolutionary tool that has dramatically impacted various industries. With the capability to simulate human cognition in everyday activities such as experiential learning, language comprehension, problem-solving, and decision-making, AI encompasses a wide range of technologies that may be applied in data processing and analysis, and automation of repetitive tasks.
The global mining industry is enthusiastically embracing the myriad of opportunities presented by AI, spanning big data processing to optimization of tedious tasks. Adoption of AI into the mining and extractive domains is pivotal to innovation and advancement in many countries worldwide.
On the African continent, South Africa is commonly acknowledged as housing the continent's most developed mining sector. In a 2020 Statista report, the country was listed in the top ten mining countries in the world, with a mineral production value of $32.5 billion. South Africa has been proactive in adopting cutting-edge technology such as AI, data analytics and automation techniques for its drilling and blasting mining activities, thus propelling it to the forefront of the mining sector within the African continent.
This comes as no surprise; the country reportedly possesses the highest number of AI specialized companies in Africa, as of 2022. This also underscores the impact of African governments’ limited response or indifferent attitude towards establishing an AI ecosystem. In many instances, the standard of living of people is adversely affected as well as economic productivity across various industrial sectors.
One characteristic of modern mining is the generation of large volumes of data, and as such, heavy reliance on data analytics and machine learning is required. Incorporating AI into data processing and analysis would unearth untapped potential in exploration and extraction activities. For example, the Supervisory Control and Data Acquisition (SCADA) system is frequently relied on in the mining industry to monitor equipment, operations, mine throughput, and also make informed decisions that optimize production. AI can enhance SCADA significantly by identifying trends and anomalies which may not be so easily recognized by human operators. AI algorithms can also aid in predictive maintenance, by pointing out equipment likely to require maintenance or repair.
The SCADA system forms part of a larger concept known as “Smart Mining”. Smart mining is the integration of technologies, data analytics, and automation in the mining sector. Cutting-edge tools and strategies are employed in the optimization of various mining activities, spanning exploration and extraction operations to processing and transportation. This promotes the smooth running of cost-effective mining operations, and a safe working zone with minimal environmental damage.
The driving technology behind smart mining is the “Internet of Things” (IoT) which operates via a network of internet enabled devices and sensors. The convergence of AI and IoT – termed as Artificial Intelligence of Things (AIoT) – results in intelligent decision-taking and higher productivity.
Smart mining in Africa has only just started to gather momentum in recent years. Amid the current era of the Fourth Industrial Revolution (4IR), many African mines are envisioning their mine sites being empowered by digital technologies. South Africa pioneers in this initiative with the development of products such as the SmartMine IoT Platform by the Schauenburg Systems company. The product is said to enhance productivity in the mining sector via innovative business intelligence and data modelling tools. The South African based Bosch Rexroth Smart Mine company is also running at the forefront of AIoT enhanced mining by offering mining solutions aimed at boosting business growth through digital transformation across Africa.
One of their breakout AIoT mining solutions is the “Smart Conveyor”, established in Africa at the peak of the COVID-19 pandemic. This cutting-edge technology introduces a conveyor belt system operating with cloud-based sensors designed to identify faults springing up along the conveyor. This technology instantly identifies the fault location thus eliminating the need for manual fault detection.
Indeed, South Africa has embraced the implementation of AI across various industrial sectors, but other countries such as Kenya, Egypt, and Nigeria are also taking strides to move beyond the nascent stage of AI adoption. Notably, Mauritius was the first African country to publish a national AI strategy back in 2018. Kenya followed suit in 2019 by publishing its national AI strategy, highlighting blockchain and AI as key business enabling technologies. Egypt has also set up a National Council for Artificial Intelligence and an African Working Group on AI to forward the course of a cohesive African AI strategy. In Nigeria, the NGO, Data Scientists Network, formerly known as Data Science Nigeria, has been successful in providing education on AI and data science in the rural parts of Africa.
The mining landscape is seeing a profound reshaping in the era of 4IR. The stage is set for African mining sectors to reap the benefits from the multitude of opportunities being offered by AI. South Africa has pioneered the way, and hopefully with time, other African countries will follow suit and drive their mining sectors forward.
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