Emerging horizontal Intelligent IoT platforms such as Azure IoT have the real potential to scale back solution development time and cost. Microsoft expressed that customers embracing Azure IoT with Percept can run pre-built AI applications end-to-end in as less as 10 minutes and build customized functional prototypes in under 30 minutes.

These awesome numbers have resulted from standardizing the key design elements of each IoT component. Reducing the component variability simplifies integration, but ultimately customers must choose from a limited number of certified products. So, large-scale adoption of Percept, Azure IoT, and other horizontal IoT platforms requires us to embrace a very robust and rapidly expanding set of compatible devices with flexible programmable models. It might take a few years, but horizontal platforms like Azure IoT & percept can potentially turn the 80% Intelligent IoT project failure rate into an 80% success rate.

Why do so many enterprise IoT projects fail?

Microsoft interviewed 500+ customers about the recent IoT projects  and noticed that “less than 20% percent of the total proofs of concept that were developed ever even moved to production deployment.” Whereas all the surveyed customers complained that there are no end-to-end IoT manuals or blueprints to follow.  90% of them have indicated that matchmaking (missing parts finding) was a huge complication. Developers have to find, modify and integrate hardware and software components from multiple vendors, stitch them into enterprise services, ensure enterprise-grade security and maintain the whole stack for many years–all without instructions (blueprints) to follow. Hence, the 80% failure rate.

“Solutions” are not the solution.

In the current scenario, most of the  IoT suppliers & integrators aim to reduce the complexity by explicitly offering pre-integrated vertical industry solutions. The convincing sales pitch is, “Partner with us, and we would take care of everything for you.” This approach works perfectly only when customers' business requirements are closely matched with pre-integrated capabilities. Unfortunately, this is rarely the scenario. Customizing the pre-integrated components to each customer’s unique physical infrastructure, operational processes, workflows, and business systems usually require modifying many pre-integrated components. The butterfly effects of these intrusive alterations reduce the advantages of pre-integration. “All-Purpose” solutions seldom fit customer requirements right out of the box and customizing pre-integrated components is generally costly and risky.

Horizontal IoT platforms

An IoT platform combines both plug-and-play hardware and software components with fast domain and customer-specific customizations. Although IoT platforms from Microsoft, AWS, Hitachi, Google, Pelion, Software AG, and others have been rapidly growing for years, none have solved the entire problem. Visibly, the failure rate for enterprise IoT deployments remains stuck at 80%. Transitioning from 80% failure to 80% success requires horizontal IoT platforms that completely nail down these three key characteristics:

  1. Works right out of the box – basic horizontal functionality with very little or no coding
  2. Hassle-free customization – the ability to develop with mainstream IT tools and expertise
  3. Robust ecosystem – a good selection of plug-and-play components for prototyping and POC

Azure IoT and Percept

After a decade of steady progress, Azure IoT is getting closer to delivering an IoT platform trifecta, an end-to-end functionality just a few minutes after unboxing, a goto selection of compatible components, and hassle-free customization. Azure Percept, a logic layer on top of Azure IoT, considerably advances all the 3 features and is an attestation for Microsoft’s consistent Azure IoT product. At Cloud4C, we have analyzed Azure IoT and percept thoroughly, and here is our take on each element of the trifecta.

Works “right out of the box”

Percept’s principal design goal is to streamline AI model deployment on accelerated IoT devices. Percept Studio, the hub of the offering, integrates Azure AI, Azure Machine Learning, Azure Cognitive Services, Azure IoT management services, and Azure Live Video Analytics. The whole stack functions end-to-end, from sensors to the cloud, wanting no coding when used with the Azure Percept Development Kit. The Percept kit consists of two hardware modules: an AI-accelerated edge computing device (NXP iMX8m, quad A57) and a Percept Vision camera (Movidus Myriad X MA2025 VPU, 0.7 TOPS). The Vision module is also available independently, as is the Percept Audio module with a built-in cluster of four microphones.

Contrasting to other IoT prototyping hardware, the Percept Development Kit is compatible with the 80/20 1010-series industrial building system, often characterized as “The Industrial Erector Set.” Customers can use Percept modules as-is in real-world industrial environments for proofs-of-concept trials and, in some other cases, production deployment. Traditional assessment and prototype boards and boxes designed for use in development labs require custom hardware for field use. In contrast, developers can latch Percept Development Kit hardware directly into industrial environments, terminating the need to develop new hardware enclosures and boards.

Microsoft exudes confidence that customers can get pre-built AI applications up and running on the AI-accelerated Percept Development Kit in just 10 minutes and create customized functional prototypes in under 30 minutes.

Easy customization

Although Percept ignites basic end-to-end functionality in no time, every Industrial Internet of Things (IIoT) project needs some sort of domain-specific and enterprise-specific customization to achieve business requirements. Customization complexity is a prime cause of IIoT project failure, so the big question enterprises should ask when evaluating any horizontal IIoT platforms is, “How easy is it to tailor the whole end-to-end stack to my business requirements?”

Horizontal IoT platforms streamline customization by extracting the cryptic intricacies of embedded programming so that IT personnel can use familiar models, languages, tools, and DevOps practices across the whole stack, from devices to clouds. Uniform architecture makes it much easier for compliant devices to seamlessly plug-and-play with high-level, IT-friendly services and development tools, thereby simplifying customization. Have a lot at some of the services that comprise the Azure IoT ecosystem and the device platforms that are compatible with them:

IoT services:

  • Azure IoT Hub – Connect, authenticate, provision, update and manage devices
  • Azure IoT Central – Connect, build and deploy apps
  • Azure IoT Edge – Deploy cloud workloads, AI modules, and custom services via standard containers
  • Azure Digital Twins – Build digital models of real-world things and processes
  • Azure ML – Build, train and deploy machine learning models

Device platforms:

  • Azure Percept – Hardware and services for deploying AI on accelerated devices, built on Azure Cognitive Services, Azure ML, Azure Live Video Analytics, and other services
  • Azure Sphere – Hardware and services for secure edge devices
  • Azure RTOS – Embedded OS compatible with Azure IoT Services (based on ThreadX)

Azure IoT services streamline device programming, empowering developers to write code that adds business value rather than customize operating systems, network stacks, security, and other IoT plumbing. However, in many IIoT use-cases, the accessible set of compatible IoT device platforms unsupportive to the essential features that industrial IoT applications require.

Robust ecosystem

Azure Percept’s industry take-up fundamentally depends on the size and flexibility of its ecosystem. Only the three hardware devices listed above are available at launch: Development kit, Vision, and Audio. Vision and audio applications are globally applicable in industrial applications, so the starting product offering makes sense. Although, industrial IoT applications need a much wider variety of sensors. Some vision applications require esoteric cameras such as IR, 3D, high resolution, fast motion, low light, small size, and low power. Other IIoT applications require a broad selection of specialized acoustic sensors–seismic, for example. Hundreds of sensor types other than vision and sound are also applicable in AI-based analysis. Azure IoT customers need a broad and expanding ecosystem of compatible edge devices.

The Azure Percept partner environment currently includes Aaeon, Ability, Advantech, Arm, Arrow, Aruba, Asus, Avnet, Intel, Lenovo, NXP, TKE, and Sharp/NEC. Asus is the OEM for the three initial Percept modules. The excitement around the Percept launch is real, and we can soon see additional devices shortly.

Cloud4C’s Azure COE’s exclusive exploration with Microsoft’s Azure Percept has given us plenty of insights and innovative ways to use this platform to help customers quickly get to desired business outcomes by accelerating the development of edge AI solutions. We can get you to start piloting and testing your own edge AI solution in only minutes. Contact us to know more.

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Team Cloud4C
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Team Cloud4C

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