India is fast taking significant strides in the deployment of emerging technologies that promise to disrupt traditional businesses. Enabled by the exponential increase in computing power and the availability of large amounts of data, machines are fast learning to replace humans in several areas. This intelligence is moving away from central server farms to devices and things that will soon become a part of our everyday lives.
The volume of data generated on the new web-connected systems, combined with the ability to self-enhance through increasingly sophisticated artificial intelligence (AI), could fundamentally change the way the world operates.
From a business and technology point of view, emerging technologies such as internet of things (IoT), AI, digital twin, edge and fog computing and immersive user experience will have a strong impact on India’s evolving technology and digital landscape.
Digital twin is a dynamic virtual representation of a physical object or a system across its lifecycle, using real-time data to enable understanding, learning and reasoning. IoT sensors that gather information and data such as real-time status, health and performance, and live position are integrated with a physical object. A digital twin ecosystem comprises technologies such as IoT, AI, big data and the cloud.
Fog and edge computing
As per the OpenFog Consortium, fog computing is a system-level horizontal architecture that distributes resources and services of computing, storage, control and networking anywhere along the continuum from the cloud to things. By extending the cloud closer to things that produce and act on IoT data, fog enables latency-sensitive computing to be performed in proximity to the sensors. This results in a more efficient network bandwidth, and more functional and efficient IoT solutions.
While the terms fog and edge computing are used interchangeably, the key differences lie where the computing takes place. Edge computing pushes the intelligence, processing power and communication capabilities of an edge gateway or appliance directly into devices like programmable automation controllers (PACs) whereas fog computing pushes intelligence down to the local area network level of network architecture, processing the data in a fog node or an IoT gateway.
Many IoT software companies have launched products that push the limits by embedding complex event processing, machine learning and AI in the edge/fog computing nodes to cater to this expanding market segment.
The International Data Corporation (IDC) predicts that by 2025, nearly 45 per cent of the world’s data will move closer to the network edge. Fog computing architecture is a key to enable this large amount of data to be processed, stored and transported. It also supports emerging technologies such as IoT, 5G and AI. The overall market opportunity for fog computing is pegged to rise to $18.2 billion by 2022, up from $1.03 billion in 2018 and $3.7 billion in 2019. For example, turbines are installed with multiple sensors to generate predictive maintenance alerts in the industry. These turbines, deployed in electricity generation, create terabytes of data in real time and the limited memory buffers present in IoT devices store this locally in IoT sensors. The data stored in sensors is sampled at a high sampling rate and measures electrical parameters, pressure, flow rate, etc. This is later analysed by specially designed algorithms based on turbine manufacturers’ performance data to find anomalies that may cause premature turbine failures. Meanwhile, some other failures may require tripping the system for short durations to avoid damage.
If algorithms can run on an edge computing node within the same LAN network, the response time to take preemptive actions can significantly improve in comparison to algorithms processing this data on a centralised platform on the cloud that cause delays due to network latency. So, the industry has adopted fog computing of data locally at the edge with distributed AI, which performs these real-time operations as well as improves the life of costly equipment.
A trend analysis based on key data points of long-term value is being done on a central infrastructure, on a case-by-case basis, that can process years of data using big data platforms. These hybrid architecture measures have benefited the industry by integrating the platform with the source where the data is generated, effectively improving latency, reducing data transfer costs and yet utilising the benefits of central cloud-based data analytics platforms.
Fog computing provides the following key benefits:
- Improved performance: There is a significant improvement in system performance as edge/fog computing nodes are installed in the local network, which reduces the turnaround time.
- Data security and privacy concerns: Organisations deploying IoT systems have data security and privacy concerns regarding the sharing of sensitive information on cloud platforms. In fog/edge computing, architecture data resides locally in an organisation’s networks so that the organisation has full control over its security and privacy.
- Opex reduction: Operational costs incurred on bandwidth reduce significantly as aggregating, processing and storing of data is performed locally on fog/edge computing platforms.
Virtual, augmented and mixed reality applications
Virtual reality (VR) provides a computer-generated three-dimensional (3D) environment that surrounds users and responds to their actions in a natural way, usually through immersive head-mounted displays and head tracking. Augmented reality (AR), meanwhile, bridges the physical and digital worlds by overlaying information, such as audio, text, images and interactive graphics, onto the physical environment. AR offers context-based digital information right where you need it.
Mixed reality (MR) is an overarching technology solution, which merges the real and virtual worlds. VR, AR and MR technologies are projected to grow at a compound annual growth rate of 71.6 per cent, reaching a market size of $147.4 billion by 2022. The areas of application of VR, AR and MR include overlaying live feeds with digital information, offering remote services, leveraging virtual reality technology for simulations, and highlighting the localisation and positioning of objects.
Virtual objects are recreated using computer aided design tools to model the AR experience. Equipment properties and services are exposed by IoT/MES (manufacturing equipment services)/SCADA (supervisory control and data acquisition)/ERP (enterprise resource planning) softwares and merged with virtual objects. This is then superimposed on the real-time feed of cameras to provide an enriching user experience with contextual data superimposed on the recreated AR scenes on devices such as smartphones and AR headsets.
Based on the knowledge paper, “Future of IoT”, by EY