Overview: The Need for a Streamlined Path to IoT Application Creation
IoT Applications are built from multiple diverse technology components – from sensors, data aggregators, and edge intelligence devices, to data delivery services, to application ingestion & data transformation, to data storage & MGT, to analytics and business logic code engines, to dashboard creation tools, finally, to application layers – and all of this must run in a highly secure, scalable and Always-On solution. Moreover, IoT Applications are inherently diverse – connecting disparate devices, serving different business needs, and often integrating to specialized back-end software. Adding to this complexity, IoT applications must be able to efficiently and cost-effectively evolve as application use case change, new devices or data flows are added, or customer requirements grow.
As a result of this inherent complexity, it is easy for even experienced teams to see the costs and schedules for IoT programs to get out of control, leading to disappointing results, or even abandoned projects. Many believe this to be the reason for the slower than anticipated delivery of the economic benefits of IoT. While low-cost sensors and edge processing, ubiquitous communications (WiFi, LTE, LTE-M, LoRa, etc.), low-cost cloud computing, and powerful open source software are all available, the complexity of putting together unique / bespoke applications remained a barrier to success. Simply put, the overhead and complexity of composing these entire stacks and then building custom applications on top – even when using the very nice tools from the IoTaaS providers – has been too hard.
IoT Application Enablement Platforms (AEP) squarely address exactly this issue, opening the door for enterprises, operators, and OEM to finally realize the full economic benefits of IoT.
IoT Application Enable Platform (AEP) – The Architectural Building Blocks
According to IoT Analytics, an AEP consists of eight key aspects:
- Connectivity and Normalisation- simplifies connectivity of different devices, protocols and a variety of data formats into one software interface to ensuring continuous connectivity, accurate data streaming, interaction between various devices and harmonised data formats. Simplified data transforms and normalization is an important AEP function.
- Device Management– delivers lifecycle management functionality for connected devices, including device onboarding, deployment of software and firmware updates, and configuration of managed devices.
- Database- cloud-based repository scalable in terms of data volume, velocity, variety and veracity. Top AEPs will provide multiple databases to optimize based on data types, and also to simplify cross-application communications, in effect providing data-lake functions.
- Processing and Action Management – provides a rule engine that to enable of rule-based event-action triggers, to launches diverse actions based on the real-time data streams processing. Also provide the infrastructure to host more complex event handlers.
- Analytics– uses algorithms for a variety of calculations, from basic data clustering to predictive analytics obtaining the most value from data-stream. The best AEPs will provide both no-code (automatic) as well as custom algorithm & analytics hosting & operation.
- Visualization- enables graphical display of real-time and historical data, enabling patterns and trends observed in visualisation dashboards and reports. The best AEPs will provide built-in dashboards, dashboard creation, and new Application Creation workflows.
- Additional tools– allows developers to prototype, test and market their IoT use cases by creating apps that enable them to visualize, manage and control connected devices.
- External interfaces – include APIs, libraries, SDKs and gateways facilitate integration with third-party systems and to enable leverage of the rest of the IT ecosystem.
A best-in-class AEP will not only provide a secure, reliable and scalable underlying IoT platform with all of the essential technology and service components, but will also provide a complete set of tools and workflows to enable efficient creation of unique / bespoke applications. Using an AEP, creation of sophisticated new applications now takes days or weeks – instead of months or even years. By adopting an AEP, enterprises, operators, and OEMs can much more directly apply their skills and industry know-how to in-demand customer solutions – instead of underlying complexity.
A high-level drawing covering some of the aspects of the IoT83 AEP solution is shown here:
And beyond the underlying secure, reliable and scalable platform and application creation tools, the AEP approach would be to provide a location-tracking feature instead of a more restrictive fleet tracking feature. Or, and AEP would provide Alarm & Alerts prioritization and management modules and anomaly detection and diagnostic modules & building blocks versus hard coded solutions. Tools like modules and workflows to accelerate creation of application specific Predictive Maintenance solutions enable an AEP to increase the scope and value of the “Lego Blocks” you need to realize your complete and powerful application – all accelerating you IoT value creation. So, and AEP will dramatically accelerate the creation of your “first iteration” application, but will also make it easy iteratively add layers of sophistication, connectivity to other systems, add new customer features, and much more.
For an apt comparison – think hover-craft Vs horse & buggy. It is that big a difference!
For the story on the “Criticality of AEPs for IoT”, and to better understand why utilization of AEP technology makes the difference between success and failure, download the White Paper Link Below!