As emerging technologies mature, the trend is often towards a convergence of approaches, which in turn opens up viable applications for the future world of work and for society in general. An exciting new development is the use of AI to enable and power emerging technologies. Innovations in the field of emerging technologies and artificial intelligence are transforming our world.
Emerging technology and AI can play an important role within an organisation, improving the operations and functions of an organisation, or it can be the very reason why an organisation exists. Business leaders must contend with constant updates and developments in the technological environment. They must also grasp not just how new technologies can play a role in improving the efficiency of the way the organisation works but must also understand how these technologies can enable groundbreaking strategies to drive growth.
Key emerging technologies enabling the transformation of businesses and the use of AI to power emerging technologies
The Internet of Things (IoT)
The Internet of Things connects billions of sensors and devices such as consumer objects and industrial equipment onto networks. What makes smart, connected products fundamentally different is not the internet, but the changing nature of the “things”. It is the expanded capabilities of smart, connected products and the data they generate that are ushering in a new era of competition.
Internet of Things (IoT) is being used to provide, for example, highly integrated value chain solutions connecting on-vehicle/robot sensors and other integrated devices over supply chain networks. Embedded sensors in transport vehicles, containers, and more continuously capture, share, and act on real-time data. The move is away from the traditional approach of managing orders and logistics to more mature goals of improving quality of customer service, regulations and improving security. In operations where repairs are carried out, IoT can be used to track movement of assets coming in for service, repair, and rebuild operations, and coming out of these operations. Information can be used to, for example, determine current and optimal service, repair, and rebuild times, track conformance to standard maintenance schedules, and track the “efficacy” of services based on mean time between services or repairs.
The Internet of Things (IoT) infrastructure is integrated with AI technologies to create AI IoT. AI systems analyse large amounts of IoT data and create value by leveraging data from multiple connected devices to acquire insights, forecast outcomes, and adapt to changing environments. IoT devices, integrated with AI, become more intelligent and effective, without human intervention, providing tailored services across many industries including automotive, healthcare, financial, farming and other industries.
Analytics and machine learning
With so much data being captured, one of the biggest advantages an organisation can gain is by analysing collected data and taking decisions based on identified patterns. In, for example, a car service facility, using insights gained from collected data, patterns and trends can be identified that could be used to inform decisions on types and quantities of model-specific spares to be held based on maintenance requirements, parts usage, and so on. Machine learning applications are able to uncover these hidden patterns.
In the clothing retail world, computers are being used to analyse Big Data and the information that is generated on customer spending habits, types and styles of items purchased, and demographics is being used to adapt and inform stocking policies in the warehouses and retail stores – and the algorithms are being used iteratively without much human intervention.
Machine learning and AI is being combined and used to turn volumes of passive data into actionable business intelligence. Machine learning and AI is being used to dynamically monitor and adjust for incoming orders, improve demand forecasting accuracy, and predict trends and performance.
Augmented reality
Augmented reality (AR) is a technology that overlays computer-generated content onto a user’s view of the real world, creating an interactive experience that enhances their perception of reality. AI enhances AR by providing the intelligence to process and understand the real-world environment, while AR provides a visual layer for AI to interact with and present information in. Augmented reality and AI are being used in several applications as follows:
- Pick and pack operations
Augmented reality can be used in warehouses to more efficiently locate products and pack them in outgoing boxes. One of the costliest aspects of running pick and pack operations is in training workers to navigate large warehouses and find the products they are searching for. AR glasses can paint an imaginary line on the warehouse floor to simplify the searching and training. New or temporary workers can be onboarded quickly. AR shortens the learning curve by providing new hires with constant feedback on their glasses about how they are doing and what can be improved.
- Robots
Workers sitting comfortably at their desks can wear AR glasses that let them see what is going on in a remote location – an example of this would be a worker in a central facility who is able to see what a parts transport robot in a car parts manufacturing facility sees. AR glasses can chart the paths of robots and automatic guided vehicles (AGVs) through the factory and use a robot’s strength to lift and move heavy items. Dangerous or repetitive tasks, such as loading a truck, can be delegated to robots that operate with human guidance when it comes to how to best load the items to achieve the maximum load. Additionally, logistics robots will be able to scan each product for damage, check its weight, and abide by any packaging and shipping instructions and requirements. By connecting robots with managers, internal customers can be automatically alerted if any parts aren’t available before trucks leave the factory.
- Maintenance
Fixing a problem before it happens is the most cost-effective form of maintenance. For example, in the mining industry, assets in the field such as ore-bearing delivery vehicles, hydraulic shovels, dozers, wheel loaders, drill rigs, and draglines can transmit usage data via Wi-Fi from RFID tags. (RFID stands for radio-frequency identification, a technology that uses radio waves to wirelessly identify and track tagged objects.) It works by transmitting data wirelessly between a tag placed on the object and a reader to detect and read the tag’s information. Augmented reality can assist maintenance crews in reducing asset downtime by comparing asset or parts data with the past history of other similar assets. The use of AI algorithms can then suggest, and adjust, maintenance and repair schedules, before a problem is likely to occur. For assets that are at distant locations, AR can also enable more experienced maintenance teams at central maintenance depots to see what technicians in the field are dealing with and provide timely live support or additional support as necessary based on volumes or sudden “surges” in assets requiring maintenance repair in the field.
Robotics and collaborative robots
Over the last few years robots have quickly increased their level of intelligence and flexibility as machine learning and artificial intelligence (AI) have been built in. The result of these innovations is a new style of robot that is suited to work side by side with humans, called collaborative robots or cobots.
Modern manufacturing robots are being used to complement traditional operator processes on the shop floor. These robots are designed to operate on the floor in the same spaces where shop floor workers are at work, often in collaboration with those workers. In this model, the robot is assigned a task and automatically navigates to a work location (collaborative robots can use sensors to navigate throughout the facility). When it arrives at a location it can operate machines, load and unload parts, and perform other machine-related tasks, allowing human workers to focus on other aspects of the process. The robot is then directed by the software controlling the system to the next work location.
Through the use of machine learning and AI, work is prioritised and assigned to human workers and cobots automatically, on a real time basis, to optimise resource utilisation and enhance workflow and productivity.
Emerging technologies and AI African use cases
African visionaries are using first-world emerging technologies and AI to solve third-world problems. There are several cases of AI being used in combination with emerging technologies in Africa to successfully solve African-centric problems. Two examples of these use cases are as follows:
Healthcare (Ghana): The delivery of healthcare services in Africa is under pressure to change, yet few have a clear picture of how the industry will evolve. What is certain is that future trends will be driven by access to big data and to new models of care around driving innovative, affordable, and accessible services across the continent. While many of Africa’s 1.2 billion people are enjoying longer lives, the rise of non-communicable diseases (such as cancer, diabetes, respiratory, and cardiovascular ailments) has led to a growing recognition of the importance of digital innovation in delivering curative and preventive care.
In this regard, a healthcare organisation, minoHealth AI Labs, based in Ghana, uses artificial intelligence, machine learning, and deep learning for medical forecasts, diagnoses, and prognoses. The system currently handles conditions including breast cancer, diabetes, pneumonia, fibrosis, hernia, cardiomegaly, emphysema, oedema and effusion. The artificial intelligence systems are trained on datasets of the various conditions. After training, these systems are tested on reserved data. They are mostly computer vision systems, which simply take medical images such as chest X-rays and mammograms as input and then analyse them to diagnose the various conditions. The AI systems are accompanied by data analytics systems and cloud computing, which help collect patient health data and then analyse them to discover patterns and generate helpful health statistics. MinoHealth AI Labs is also carrying out research using AI to improve and save lives.
Smart farming (Kenya): Timely and accurate information on fertilisers, seeds, weather, crop management, and markets is essential information for both large- and small-scale farmers operating in rural areas throughout Africa. Rural smallholders account for more than 70% of the food produced in Africa. With the world’s population expected to rise by an additional two billion people by 2050, and with more than half of that increase expected to occur in Africa, food will be in ever greater demand.
Smallholder farmers find themselves at centre stage when it comes to bringing the new agricultural revolution to Africa; a revolution that must start with data. Given the importance of data, it is vital that smallholder farmers are transformed into a knowledge-based community connected and powered by precise information. UjuziKilimo is an agricultural technology company, based in Kenya, that modernises African farming by enabling small-scale farmers to practise precision agriculture and access actionable, high-quality agricultural information for improved yields.
AI applications encompass a spectrum of innovations. At its core, AI integrates advanced algorithms with data from sensors, IoT devices, and machinery used in farmers’ fields to optimise farming practices. In crop management, AI analyses vast datasets to provide real-time insights into soil health, pest infestations, and crop diseases, thereby enabling timely interventions and reducing yield losses. Weather forecasting powered by AI enhances resilience against climate variability, improving decision-making for planting and harvesting schedules. AI-powered machinery equipped with computer vision and machine learning capabilities further automates tasks like planting, harvesting, and sorting, improving efficiency and reducing labour dependency.
KEY TAKEAWAYS
- An important new development is the use of AI to enable and power emerging technologies.
- The continued and increased use of AI, together with emerging technologies, is opening up new horizons for organisations in terms of being able to provide agility, speed, and differentiation in serving customers.
- Several emerging technologies including the Internet of Things, analytics and machine learning, augmented reality and robotics are benefiting from the application of AI in tandem with these emerging technologies.
- There are several cases of AI being used in combination with emerging technologies in Africa to successfully solve African-centric problems.
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