24 Apr Challenges with deploying an end to end IoT solution – Under development

By : Mehul Gupta

What is an end to end IoT Solution?

• An end to end IoT solution consists of multiple layers of solutions. Starting with device and connectivity layer, this layer consists of devices, machines, equipment, equipment systems, SCADA, PLC, Enterprise systems and business system. Read more about it here.

What are the typical challenges while deploying an IoT solution?

• It is often hard to imagine for a company the scope of work and challenges it will face while successfully deploying an IoT solution especially those who have no experience in deploying similar solutions in the past. Therefore, before proceeding to delve into the challenges, it is important to note that hiring trained and certified IoT consulting companies would certainly help minimise any risk while deploying the solution.
• The challenges while deploying an end to end IoT solution starts with the device and connectivity layer. In this layer, dealing with the thousands of devices is the primary issue. To best understand the challenges let’s take an example of a factory where there are thousand identical devices for monitoring the environment. Each device then has a hundred properties and transmission frequency (frequency at which data is transmitted from the device to the IoT platform) of 0.5 Hz which is the same as 1 reading every 2s.

• Using these values, the operation per seconds, i.e. the amount of operation the IoT platform would need to perform every second OPS = number of devices x transmission frequency, is 500. Whereas the property writes per second (PWS = total properties X OPS = 100 X 500) then becomes 50000.
• Hence, it becomes easier to imagine the challenges that arise from managing the throughput of the content from these devices at an incredible pace. Also, with these high number of operations every second, the IoT platform’s architecture needs to be able to handle the large amounts of data incoming every second. Then perform the necessary operations in parallel to be able to provide the user with real-time insight into the performance of the smart connected devices, which don’t have to be limited to a device it can be production lines, equipment, equipment systems and even business systems.
• Moving onto the application layer, with the large amounts of data incoming it would be not possible for a single individual to sit and analyse the data as it comes in. Therefore, the platform needs to provide the ability to program logic, thus enabling automatic alert generation based on the logic.
• As with the any IoT platform, it also needs to provide secure options for remote monitoring of assets and devices while also providing diagnostic services to end users, including remote troubleshooting and automatic creation trouble tickets.
• The challenges while deploying within analytics layer is primarily being able to predict failures before they occur, integrate with knowledge-based systems, and integrate augmented-reality technology into the field service processes. These often require some cutting-edge technology such as edge computing and edge analytics, also a whole suite of powerful machine learning algorithms.

What are some of the ways, an industrial IoT platform like ThingWorx addresses these issues?

• A poor architecture results in a difficult deployment, costly integration between components with each upgrade, and mixed technologies that limit future flexibility and introduce multiple points of failure. Hence, ThingWorx an industrial IoT platform provides a connected and distributed architecture to combat this issue.
  • Connected—a good connection with assets enables the platform to coordinate data monitoring, health monitoring, proactive maintenance, software management, and remote service.
  • Distributed—a distributed architecture allows for global management where consolidated statistics and KPIs across all locations are desired and provides local managers with focused and real-time information.
• When you choose ThingWorx to support your company’s IoT business processes, the deployment architecture has to meet your company’s requirements for security, scalability, performance, interoperability, flexibility, and maintainability. Hence, ThingWorx provides support for several technologies and solution architectures to ensure continued support for organisations with small to enterprise level production systems.
• The ThingWorx Connection Server is a server application that facilitates the connection of remote devices and handles all message routing to and from the devices. The ThingWorx Connection Server provides functionality, such as scalable connectivity over WebSockets using the ThingWorx Communication Protocol. This helps to address the issues surrounding the management of thousands of connections from devices to the ThingWorx IoT platform.
• To deal with the large amounts of data the ThingWorx platform offers a pluggable data store model, which allows every customer to choose the database that best suits their requirements—from small implementations for demo and training environments to highly-available, high- volume databases that support thousands of transactions per second. Example of databases supported are H2, PostgreSQL, SAP HANA, Cassandra and Microsoft SQL.
• The ThingWorx Platform includes a Mashup Builder, which is the tool you use to create your visualisation web pages in ThingWorx and is where individual Mashups are defined (A Mashup is a ThingWorx web page). The Mashup Builder is designed to be used by a content developer who has knowledge of the implemented ThingWorx model and allows you to combine the data services available within ThingWorx with a set of visualisation components, called Widgets, to create unique web pages that can combine data from multiple sources. You also define Style Definitions and State Definitions entities within the Mashup Builder. Styles and States are used to control the look and feel, such as colours, fonts, and colour contexting, of individual Widgets in your Mashup.

• To address challenges with analytics layer, ThingWorx Analytics provides tools for applying supervised machine learning to your data and embedding advanced analytics insights into your smart, connected solutions. These tools can help you analyse and understand the data you collect from your connected devices. They can analyse what is happening right now, predict what might happen next, provide causes for future conditions and help prevent issues now.