The Internet of Things (IoT) is becoming the superstructure of modern life. But before we can truly harness its many opportunities, we will have to address its challenges. Machina Research, global advisors on machine-to-machine, the IoT and Big Data, predicts that by 2025, there will be 27 billion connected devices, and the IoT will be worth $3 trillion in revenue.
What will the data generated from all these devices mean to an enterprise? Well, at its best, it could mean an opportunity to reimagine every process in order to optimize costs and resources at every level, and develop new products and services, which may have not yet been imagined. Behind the exciting possibilities of IoT is a mammoth task, when one considers the quantity of data to be analyzed, and the corresponding computing power needed.
In the manufacturing industry, where machines have hundreds of moving parts, it would mean access to terabytes of data per minute. The data collected could include GPS coordinates, weather conditions, images, videos, and more. For this staggering quantity of data to be analyzed, enterprises will have to rethink computing architecture and tools. And enterprises will truly be able to leverage IoT only when they are able to extract the utility value of their data.
Challenges posed by the ever expanding Internet of Things
One of the things that will hold us back from fully experiencing the benefits of IoT is the compartmentalized way of collecting and storing data. It is only when enterprises gain complete control over their data that they will be able to glean deeper insights. Another area of concern is that of data sharing. For instance, the temperature of a turbine would be relevant to the turbine manufacturers, the user, the supply chain network, and the regulator, but unless this data is made accessible to the relevant stakeholders, they will not be able to extract the insights it has to offer . Other challenges in the adoption of IoT that we will dwell on in this post are security, integration, implementation costs, and culture.
Security: While we prepare to embrace increased connectivity that IoT offers, data privacy and device security for tablets, PCs, smartphones, wearables and data encryption for microcontrollers, will need to be tightened. According to an Internet IoT Survey by Machina Research in 2016, 58 percent of enterprises in the US were concerned about security. Data is being transmitted outside the enterprise network to the cloud, and hackers can try to access it at any point – from when it is being gathered to where it is at rest, and in between. Prpl, an open-source, non-profit foundation focused on enabling next-generation datacenter-to-device portable software and virtualized architectures is already trying to address this security concern at the design stage of products by ensuring ‘trust readiness’ for the silicon chip within a device. In the ‘Trust Ready’ approach, OTrP (Open Trust Protocol) ensures that a connected device is on a trusted path, is running authentic manufacturer-installed software, and operating in its intended state, so a server can ‘trust’ the device and the device can trust it is accessing appropriate services . To further barricade against potential attacks, enterprises can ensure that their IoT devices are operating on updated systems and firmware, and that non-compliant systems are prevented from entering the network. With time, organizations will gradually move to a central, device-agnostic security solution that is easy to manage and control.
Complexity of integration: With the large number of devices, apps, and quantity of data generated, integrating sensors and data capture methods into existing systems and software is a challenge. And one that the old infrastructure may be unable to handle. For instance, imagine digital sensors on analog connection now having to manage large volumes of data and that too in real-time.
To integrate existing systems with IoT, enterprises will have to adopt an API-First strategy, choose the best technology in communicating between IoT devices, leverage the cloud for integration, and adopt an API management tool to ensure security and scalability . Edge Computing, a method of adding a network layer below the cloud resolves some of the issues of legacy systems. Edge Computing reduces latencies in the network and prevents bandwidth bottlenecks. More recently, it has been recognized that if IoT must succeed, the current architecture of products will need to be reworked to collect, transmit and store data.
Cost of implementing IoT: While the cost of sensors is falling, the costs of managing underlying networks, cloud storage and analyzing data is not. However, in the long term, implementing IoT is actually profitable as found by MPI’s 2017 Internet of Things Study. According to the study MPI, a US-based research and advisory firm, manufacturers were able to increase productivity by 72 percent and profitability by 69 percent after implementing IoT in their plant and processes.
Cultural hurdle: As IoT becomes increasingly pervasive, more and more jobs will become redundant. Ensuring people are ready for the change – enabling them to prepare for it, and guiding them as they transition to intelligent tasks that machines cannot do – can be a daunting task for enterprises. But if done right, it can increase productivity and profitability. A case in point is motorcycle manufacturer Harley Davidson. A few years ago, they found that their core customers were aging, younger people wanted to ride different bikes, and they experienced intense competition. In 2010, Harley addressed their concerns by introducing IoT into their manufacturing process and began a large-scale restructuring process. The results were impressive. 80 percent faster decision-making due to workforce empowerment, continuous asset management that facilitated better decision-making, over six percent increase in production, and improvement in profitability by three- four percent.
Even with challenges, IoT will continue to evolve rapidly as technology advances. Enterprises will be able to derive greater value from the large quantities of data amassed from devices, especially orthogonal data (which can be used without effecting other program functions). This data will lead enterprises to ask farsighted questions, change business processes, make smarter insights-driven decisions, and in some cases even locate opportunities to launch entirely new disruptive business models. The possibilities that IoT has to offer are definitely exciting. And yet, these opportunities can’t be unpacked and tested in isolation. This is where platforms such as the Annual Meet of the New Champions, at the World Economic Forum in China enable stakeholders like the government, enterprises and individuals to participate and shape the discussion on IoT with a focus on inclusion.