The number of interconnected devices and the consumption of data is growing at staggering rates. According to IDC forecasts, we can expect 55.7 billion interconnected devices by 2025 worldwide, out of which 75% would be connected to an IoT platform. Moreover, the data generated from linked IoT devices would reach 73.1 ZB by 2025. The processing of this whopping amount of data is clogging centralized networks and will further overwhelm them in the future.

Edge capabilities will help enterprises avoid network, storage, and bandwidth issues. They help analyze and act on the data where it’s generated, which triggers instant decisions, avoiding the time and lag limitations. Edge solutions are already being used across industries – healthcare solutions, retail, agriculture, transport logistics, and industrial operations like oil and gas and mining. The unpredictability and complexity of the real world demand disruptive solutions to start at the edge.

Organizations can seize valuable opportunities by applying the logic of edge computing to operating models. It will help businesses innovate faster, run more efficiently, get more value from ecosystem partnerships, effectively manage risks with fragmenting markets, and enable faster response to changing local preferences. Apart from being uncertain, customer preferences are also changing differently in different markets. Pushing decision-making authority to the edge will empower organizations to handle such ongoing changes with ease.

Maturing technologies like Cloud and 5G are the enablers for edge, and integrating all of them provides opportunities to deliver powerful use-cases. Microsoft, Amazon, IBM, Intel, Cisco, and Google are key players in the edge market. Huawei, Dell, GE, and Hewlett Packard Enterprise are some other important players.

Major Growth Drivers

The global edge computing market which was valued at 2.94 billion U.S. dollars in 2019 is forecasted to reach a value of 68.71 billion U.S. dollars by 2030 and is expected to grow at a CAGR greater than 35% (Source: Statista). Some of the major growth drivers are:

• The exponential growth and importance of data in businesses
• The growing ubiquity of IoT devices across industries
• Increasing load on cloud infrastructure
• The advent of 5G networks
• Convergence of cloud, AI, Robotics, AR-VR, and overall digital tech ecosystem
• Demand for low-latency processing and real-time automated decision-making solutions

Edge Computing Market by Region

North America is the largest market for edge computing, accounting for 46% share of the total market value, and it will continue to grow significantly. However, the Asia Pacific market is expected to witness the fastest growth in edge compared to the rest of the regions with the highest CAGR values during 2022-2028. This skyrocketing growth can be attributed to the evolution of smart cities, the development of 5G network infrastructure, untapped market opportunities, and increasing investments in emerging economies.

Source: Grand View Research

Major benefits of edge

• Latency– Situations where even milliseconds matter and that require quick response times, low latency, and critical real-time decision-making will benefit significantly from edge solutions. For example, in manufacturing, detecting a safety issue and being able to take immediate action is critical.
• Bandwidth- Bringing AI, ML, and advanced analytics to the network edge will help smarter systems to operate more independently and reduce bandwidth and storage needs. For example, AI and ML can do more complex analyses beyond rule-based alerts in a remote monitoring system by identifying other important changes in the environment and sending insights accordingly.
• Reliability and business continuity- One of edge computing’s predominant value propositions is bolstering applications requiring low latency. Edge solutions can eliminate lag in VR systems operating in the field, like those used by deployed troops or remote workers. They can also operate autonomously in environments with unreliable network connectivity.
• Storage– Edge computing is useful where a lot of data is generated and not all data is valuable, rather situation-based data is needed, for example – video surveillance. Edge computing enables intelligent data sharing—for example, only the unique/relevant data is uploaded which reduces storage requirements, networking, and costs.

Applications in different industry segments

Healthcare 

Edge computing in healthcare can go a long way in saving lives and decreasing mortality rates. It is making access to quality care easier by helping doctors provide care to areas with poor connectivity and healthcare facilities. Enabling remote patient monitoring, telehealth services, and drone delivery of lab supplies are some of the applications.

Applications:

• Transforming patient experience in the ambulance and saving lives by transmitting critical real-time information to the emergency room personnel, enabling hospitals to prep the room according to specific case needs.
• Faster, more accurate diagnoses in hospitals through the integrated edge, AI, and ML solutions.
• Enabling medical devices to respond immediately to sensor data, controlling an artificial organ, sending alerts to doctors, and triggering required actions.
• Creating intelligent operating rooms for surgeries with more efficient processes and better patient care.

Retail, warehousing, and logistics

Edge-enabled intelligent stores can help retailers make smart real-time decisions through video analytics to drive a state-of-art frictionless customer experience. AI-powered edge solutions help eliminate stockout, improve operations and optimize merchandising through rich insights generated about in-store customer behavior. Point-of-sale systems (POS) are being transformed by retailers and fast-food restaurants with edge computing.

Applications:

• Real-time and context-specific personalized recommendations and promotions to customers via interactive screens or smartphones as they walk around the store increasing sales opportunities.
• In-store cutting-edge immersive experiences- Transforming customer experience through virtual try-on of clothing or makeup in apparel and beauty segments with augmented reality.
• Guaranteed security and theft prevention at automatic pay stations using computer vision at edge computing, triggering actions in real-time in case of abnormal situations.
• Empowering autonomous shopping through fast and flawless walk-out check-out, smart cabinets, etc.
• Creating smart shelves through cameras and sensors for real-time stock monitoring to optimize shelf capacity and reduce wastage (including automatically ordering new stock where needed).
• Real-time track and trace of goods in the supply chain and advanced predictive maintenance.

Banking and Financial Services

Edge solutions offer a range of opportunities to financial institutions to maximize revenue generation and reduce costs. Edge helps banks use real-time analytics to understand their customers better, thus enabling them to deliver world-class customer experiences.

Applications:

• Hyper-personalized services through the advertisement of relevant financial products and services by retail banks lead to high consumer engagement.
• Real-time cybersecurity through AI-enabled analytics allows pre-event detection and prevention of fraud like gaining access to the bank account through Authorized Push Payment scams.
• Preventive detection of potential fraud at transaction sites like ATMs alerts on suspicious behavior through facial recognition software in real-time to ensure customer safety.

Edge has applications in almost every other industry segment as well- energy and utilities, agriculture, manufacturing, gaming, and others where we expect to see many more interesting use-cases in the upcoming years.

Challenges

• Edge solutions raise cybersecurity and privacy concerns as they involve several technologies and components. A lot of edge devices collect personally identifiable information and don’t encrypt data natively which makes them the weakest link. Enhanced cryptographic techniques and advanced technologies need to be deployed to ensure data security while implementing edge solutions.
• The presence of legacy industrial systems might become a restraint, making integration with newer solutions more challenging, and concerns about information security impact the adoption of new technology.
• Heavy initial capital investment is required for availing the necessary infrastructure, expertise, and R&D in edge-enabled software frameworks.
• The lack of a proper set of edge monitoring tools to continuously monitor, identify and report issues faced by remote applications
• The absence of standards or broadly accepted architectures for edge computing and lack of complete awareness about the scope and use cases of edge computing are a few other reasons that come in the way of adopting edge.

In the emerging landscape of edge, along with key technologies like 5G, AI is a game-changing convergence opportunity. This seismic breakthrough will help organizations optimize their operations, improve customer satisfaction, redefine employee experiences and create differentiated business models. If utilized rightly, the impact on innovation, productivity, and user experience could be profound. While barriers to adoption remain, rapid innovations in edge security, governance, standards, and framework are a few ways to overcome challenges. Identifying clear use cases, ensuring security, building internal skills, and cost-benefit analysis will help move forward.