IoT solution development is complex. In many cases, development entails combining expertise from a number of different areas such as embedded system engineering, connectivity solution design, big data handling, application development, and data encryption techniques. Each area demands a specific array of competences and proficiency to function within its own realm. Furthermore, a varied skillset with diverse knowledge is required to develop a complete solution that blends offerings across all of these areas. But within these areas what are the key building blocks of an IoT solution?
The breakdown of IoT solutions into key building blocks was recently analyzed as part of an industry white paper published by IoT Analytics with the title “Guide to IoT solution development”. In the paper, the analysts discuss the IoT Solution development process across 5 major phases:
According to the paper, developing end-to-end IoT Solutions involves multiple layers that fuse together various components. In many cases OEMs are unaware of the complexity in IoT Solution Development.
“When we started our IoT implementation effort we had no clue what we needed and who to approach – to be honest, we didn’t even know what we were looking for.” IoT Project Manager at a Machinery OEM.
The paper outlines how IoT needs to be thought through from end-to-end or device-to-cloud. On a high level there are 5 major layers of an IoT solution including one cross-layer: Device, Communication, Cloud Services, Applications, and Security.
1. Device layer:Adding MCUs and firmware to basic hardware (e.g., sensors and actuators) creates “simple” connected devices. Adding MPUs and OSs makes these connected devices “smart”.
2. Communication layer:Enabling communication to the outside world through various connectivity networks gives the devices a “voice”.
3. Cloud Services layer:Ingesting, analyzing and interpreting the data at scale through cloud technologies generates “insights”.
4. Application layer:Connecting and enhancing these insights to the greater ecosystem through a system of engagements enables “action” through a vast range of new applications and connected services.
5. Security cross-layer:Securing an IoT solution is an element of such importance that it merits an established “foundation” in each of the other building blocks.
Each layer is made up of components that bring the end-to-end solution seamlessly together.
IoT Analytics’ 2016 IoT platforms market report reveals that some companies offer more components than others and together with their partner ecosystem some can provide complete end-to-end IoT solution support. However, with 360+ competing platform providers in the market today it can be difficult to understand what they really offer. To assist companies in better understanding the offerings of IoT solution providers, the IoT Analytics white paper showcases a high-level comparison of 8 major IoT solution providers including Microsoft, Amazon, IBM, Intel, GE, Google, PTC and SAP. The comparison breaks down each layer into components and highlights examples to create a clearer picture, for example:
• Operating System: Offers low-level system software managing hardware and software resources and providing common services for running system applications e.g., Windows 10 IoT.
• Modules and Drivers: Offers adaptable modules, drivers, source libraries that reduce development and testing time e.g., AWS IoT Device SDKs.
• MPU / MCU: Offers multi-purpose programmable electronic devices at microprocessor or microcontroller level e.g., Intel Atom processors.
• Connectivity Network / Modules: Offers connectivity network / hardware modules enabling air interface connectivity e.g., AT&T M2M, Telit IoT Modules.
• Edge Analytics: Enables time-sensitive decisions, local compute, analytics on a smart / edge device e.g., Cisco Fog Data Services.
• Edge Gateway (hardware based): Enables manageability, security, identity, interoperability based on a Cloud enabled hardware device e.g., Dell Edge Gateway 5000.
3. Cloud Services:
• Storage / Database: Cloud based storage and database capabilities (not including on premise solutions) e.g., Azure SQL.
• Device Management: Enables remote maintenance, interaction and management capabilities of devices at the edge e.g., Azure IoT Hub.
• Event Processing & Basic Analytics: Processes events and handles big data analytics e.g., Azure HDInsight.
• Advanced Analytics: Performs advanced stream analytics and machine learning e.g., Azure Machine Learning.
• Visualization: Presents device data in rich visuals and/or interactive dashboards e.g., MS Power BI.
• Business System Integration: Enables integration with existing business systems e.g., Azure Logic Apps.
• Development Environment: Offers an integrated development environment with comprehensive SDKs for creating applications and services e.g., MS Visual Studio.
• Physical Protection, Firmware Attestation: Protects / verifies the integrity of peripherals / firmware and detects malicious changes e.g., Intel Trusted Platform Module.
• E2E Encryption of Data & Communication: Secures data / communication through digital certificates and public-key encryption e.g., Symantec SSL, TLS, X.509 certificates.
• Privacy Management, Data at Rest: Encryption software that protects information that cannot be deciphered easily by unauthorized users e.g., Azure Disk Encryption, Key Vault.
• Application Identity & Access Management: Set of processes and services that stores directory data and manages communication between users and domains, including user logon processes, authentication, and directory searches e.g., Active Directory, Identity Manager.
Understanding exactly what is required on a component level for your IoT solution can ease development and integration issues for your connected solution. However, as the IoT Analytics’ database of 640+ Enterprise IoT projects shows there is clearly no one-size-fits-all approach to successful IoT solution development.
For a consistent methodology to steer your organization through the challenging process as well as other best practices for OEMs, ODMs, and device manufacturers check out the IoT Analytics’ “Guide to IoT solution development” white paper which is available for download free of charge.
§ Smart Device:Enables edge analytics, time-sensitive decisions & local compute. Maximizes security, manageability, interoperability, solutions reliability and reduces bandwidth
costs. In many cases, cloud enabled smart devices are equipped with a natural user interface. Note: MPU = Microprocessor.
† Edge Gateway:May also be classed as a Smart Device.
‡ Simple Device:Generates data, performs instant actions & transmits data. Typically has constrained resources, low hardware costs, basic connectivity, basic security/identity, and no/light manageability. Note: MCU = Microcontroller.