Unlocking the Power of IoT Data at Scale

Tushar Sachdev, Executive Vice President and Chief Technology Officer
Sep 26, 2018 11:46:50 AM

As KORE recently shared, there are six consistent challenges that are preventing organizations from fully realizing efficiency and market differentiation by way of IoT implementations. One such struggle is moving from PoCs and concepts to industrial scale applications. There is tremendous potential to be unlocked from the data that devices will transmit, but doing this at scale requires some serious design.

Through extensive research with organizations in a wide range of verticals, we have come up with five areas where future-proof design matters most:

  • Device Integration: IoT devices will be either purpose-built for specific use cases or will be industry standard devices. Integration with them requires an understanding of the messaging protocol (MQTT/AMQP/etc.), port management and appropriate listener service. However, designing them for scale requires one to think through what the future set of devices could potentially look like, frequency of data transmission, IP considerations and IoT security (which you will see as a common thread throughout my posts – security first and security by design!). It is essential to segregate device-specific nuances from the common design model in order to accommodate a large number of variations in the future.
  • Data Normalization: The next step answers the question, “Now that you have it, how can we make sense of this?” Data is coming from disparate devices with subtle or large variations in formats. As a result, it is critical to be able to clean, collect and profile the data. Lack of data normalization may lead to code fixes and the problem can compound as this data flows downstream.
  • Business Computations: Creating a data-computing library from internal or external sources is essential to gain business insights. These libraries will help do the simpler computations as well as help develop statistical models to do advance predictive/prescriptive computations. In addition to this, designing for data alignment is crucial. You do not need a horoscope reading until the stars are aligned!
  • Visualization: Wide swaths of compiled data in a format that decision-makers cannot understand offers little value. By visualizing data, organizations that rely on making in-the-moment decisions are empowered to do so confidently. For example, logistics companies that manage hundreds of thousands of fleet vehicles need to see their location and drill down to incidents that may interrupt the supply chain in real-time. A visualization framework needs to enable the user to set goals, get visibility and provide prescriptive optimizations. Designing with this paradigm will create the right business and performance outcomes!
  • Workflow: Data will lead to insights. Insights will lead to actions. Adopting a platform that can enable workflows will help trigger actions in ERP systems or sometimes even back to the devices (using actuators). These can start as simple automation, but eventually these will be the foundation for artificial intelligence, based on the machine learning (or statistical computations) that I talked about in the previous steps.

Applications dealing with IoT data and triggering downstream actions are a crucial glue to leverage your IoT investments. There are technologies and platforms that enable many of the above areas. Choosing the right ones and designing for scale will enable organizations then to focus on the real business problems that they want to conquer.

Learn how KORE can position your organization to make the most of the valuable data it collects.



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