One of the fastest-growing trends in technology is the addition of internet connectivity to any device or object we can connect it to. This trend is responsible for what has become known as the Internet of Things (IoT) and will be a major fixture of the technological landscape in coming decades. In fact, by 2020 the IoTs will consist of approximately 30 billion devices, each capable of communicating directly with each other and with any relevant processes and systems.
The size of the IoT is one of the main problems with its implementation, as the amount of data generated will scale directly with the number of devices connected. Estimates indicate that the number of IoT-related messages could reach 10,000 per person per day. Having an IoT will only be beneficial if we can efficiently analyze and use this massive stream of data.
Businesses, in particular, will encounter this problem, as they strive to adopt IoT devices quickly to remain competitive. The need to create systems to collect, analyze, store, and act on the information gathered from IoT devices will be a major impediment to the adoption of IoT systems. The existing platform of Business Process Management (BPM) is an obvious choice of medium through which to connect and process IoT data. Leading BPM platforms like Appian, Pega and IBM already have much of the infrastructure needed to facilitate the integration with IoT devices, analysis and use of IoT data, but the high volume of data will have a higher than normal number of exceptions, which may put additional burden on the human workforce to handle the exceptions as the IoT network scales. The effectiveness of any implementation of IoT will depend on the robustness of the processes that are making use of the data stream. Robotic Process Automation (RPA) has the potential to improve the integrity of the data stream, which will increase the effectiveness of any business processes using the data.
RPA is the use of intelligent software to automate tasks that would normally have to be done by a human. It differs from traditional automation in that RPA has the capability to appropriately deal with unexpected circumstances, and learn from new experiences. Where traditional automation would encounter an unexpected input and stop functioning, RPA can correct the input and continue without the need for human intervention.
RPA has the potential to make substantial contributions to IoT technology by standing at the interface between the data from IoT devices and business processes. The volume of data generated by the IoT, by nature of being extraordinarily vast, will contain contradictions and inaccuracies or errors. When contradictory or erroneous data is input into a business process, either a human will be needed to correct the input, or the process will run and generate bad outcomes. With an ever-increasing IoT, the number of processes that need to be manually adjusted will become unrealistic.
RPA technology will be used to feed the IT data stream into business processes. By comparing process input data to each other and to past data, contradictions and errors can be identified and corrected automatically before being entered into processes. The result would be a system that requires less human interaction and can support a larger IoT network. In addition, the AI nature of RPA would ensure that each time a human does need to interact with the system and adjust the process inputs, the software would learn the appropriate corrections to make the next time.
The Internet of Things is the future of business and technology, but without a strong and robust set of processes (BPM) to utilize the data, and the ability to leverage RPA and the robotic workforce, you will be missing the maximum potential of your system. Princeton Blue is an industry leader in BPM, and our recent partnership with Blue Prism has given us access to world class RPA technology. We are well positioned to help you implement your process-backed IoT system.