An Industrial Internet of Things (IoT) platform, such as the Davra Platform (opens new window), comprises eight essential components, or "pillars". They are device management, data management, integrations, application enablement, digital twins, analytics, security and compliance, and edge computing.

Each pillar is essential to creating successful, scalable, and secure IoT applications. At Davra, we implement, maintain, and constantly build on each one. Some companies specialise solely in managing a single pillar - our industrial IoT platform manages all eight.

The complexity of an IoT platform is just another reason it is better to Buy and Build. Investing in an IoT platform means all you need to worry about is making a successful application. We take care of the rest.

In this article, we will delve into each pillar and explain what they do and why they are important.

Device Management

Device Management (opens new window) is the first pillar of an IIoT platform and one of the most important. Device management ensures the reliability, security, and efficiency of connected IoT devices. After all, if you remove the “things” from the Internet of Things …well, you don’t have much left.

Davra’s heritage is in device management, and it remains a core strength. In 2021, Gartner scored Davra’s device management highest among 18 platforms, including AWS, Microsoft, Software AG, and PTC.

Once you install a device on the network, you can't just forget about it. You must onboard, provision, configure, monitor, maintain, and secure devices throughout their entire lifecycle.

Continuously monitoring the health, performance, and status of connected devices is crucial. This involves collecting real-time data on metrics like device uptime, connectivity status, resource utilisation, and IoT sensor readings.

The nature of IoT devices means they require remote configuration and management. This includes updating firmware/software, adjusting device settings, and applying security patches without needing physical access to the devices. An IIoT platform must also support devices from many different manufacturers, each with different protocols and interfaces.

Data Management

An industrial IoT platform manages vast amounts of data. Data Management (opens new window) is about how that data is collected, stored, integrated, processed, analysed, and secured. Well-implemented data management ensures data is always available, efficient, and secure.

An IoT platform must store the collected IoT sensor data securely and efficiently. The Davra Platform comes with fully self-contained databases accessed through a documented OpenAPI. This includes Cassandra for Time-series data, MongoDB for document data, Redis for in-memory data and Elasticsearch for log data.

IoT sensors and devices provide data in many different formats, so it is necessary to standardise it for consistency. The Davra Platform has an API that allows users to create custom data decoders for Hex and Base64 payloads. These decoders can convert the data into useful time series metrics while saving bandwidth in constrained environments.

IoT data security controls include encryption, access control, authentication, and data masking to protect data confidentiality, integrity, and availability throughout its lifecycle.

Integrations

An IoT platform consolidates, or integrates, your existing systems into one central system. This can have a transformative impact on your business without needing to start from scratch.

Industrial environments usually consist of systems and applications such as SCADA, MES, ERP, and others. The IIoT platform integrates these disparate systems to enable data exchange, automation, and syncing of processes.

Integration also involves implementing robust security measures and access controls within the IIoT platform. This may involve integrating with identity management systems, authentication protocols, encryption technologies, and security frameworks to ensure data privacy and protection against cyber threats.

Application Enablement & Management

Application Enablement and Management (opens new window) refers to features enabling users to develop and manage applications on the platform.

Deploying cloud services presents many potential barriers to success. The purpose of an IIoT platform also known as an Application Enablement Platform (AEP), is to remove these barriers. An AEP enables organisations to create IoT applications for their business quickly and easily. The only thing the user needs to worry about is the thin layer of logic that is their application.

An AEP allows users to write and deploy custom applications, with support for different coding languages and runtime environments. Features like a web IDE allow developers to write code directly in the browser.

The Davra Platform includes a fully managed Kubernetes cluster and allows developers to deploy Docker containers into this infrastructure. API webhooks from a deployment pipeline like Jenkins or Azure DevOps can drive this, or you can deploy a built artifact through the UI.

The platform supports DevOps by linking to external Docker repos. You have the option to connect to an external build pipeline or utilise an inbuilt pipeline. The platform includes GitLab, Jenkins, and Docker repos.

The Davra Platform also has a fully documented API to interact with all its features. This allows users to expose features in an application-specific way.

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Digital Twins

A Digital Twin is a virtual replica of a physical asset, process, or system. They are made by gathering real-time data from IoT sensors and devices embedded in the physical asset. Digital twins help organisations model an asset’s state, behaviour, and performance, leading to better decisions.

Digital twins (opens new window) can help simulate different scenarios to help businesses make informed decisions and improve processes. By training a machine learning model with historical data, digital twins help anticipate failures and optimise performance.

The insights gained from the digital twin may result in changes in the physical asset or system. This creates a feedback loop where improvements in the digital twin lead to better performance in the physical world.

Analytics

Analytics (opens new window) is probably the aspect of IoT that people get most excited about, and with good reason. Analytics is what gives data meaning and context and helps us to make better decisions. Without analytics, the data just sits there in a database.

Analytics, however, is an all-encompassing term and can mean many different things. In the context of IoT, analytics can mean anything from a simple line chart to complex machine learning algorithms. When we break it down all analytics generally fall under one of four categories. Those categories are descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics.

Descriptive analytics

This is the most basic and most widely used form of analytics. Descriptive analytics makes sense of the data coming from your devices and presents it to the user.

This can be as a time series chart, KPI, or simply a status label. Examples include a sensor values (e.g. temperature, humidity) or calculated values (e.g. dew point), device status, last seen time, etc.

Diagnostic analytics

Diagnostic analytics goes a step further to understand why something is happening. It is used to inspect IoT data and identify the root causes of issues or failures.

For instance, if a machine breaks down, diagnostic analytics would involve checking sensor data to figure out why. If a particular sensor displayed unusual behaviour prior to failure, this may point to the problem.

Predictive analytics

Predictive analytics analyses historical data to predict future outcomes. Using the same example above, we can apply predictive analytics to prevent part failures in future. We can train a machine learning model to monitor sensor data to analyse trends. Once it detects that a part is beginning to wear it creates an alert and schedules maintenance.

Organisations are looking more and more to predictive analytics to offer value-added aftermarket services (opens new window) to their customers.

Prescriptive analytics

Prescriptive analytics is the most powerful form of analytics. It involves processing as much information as possible about a scenario to then provide recommended actions. This usually involves machine learning algorithms or AI. Prescriptive analytics helps organisations to create efficiencies, cut costs, optimise their processes, and mitigate risks.

Analytics Tools

Visualisation tools such as dashboards (opens new window) make it easy to identify trends, anomalies, and opportunities for improvement. Rules engines allow users to create automated workflows based on the data. Davra's Rules Engine supports complex binary logic rules via a point-and-click interface.

Platforms such as Davra's can analyse data streams in real-time without storing the data first. Real-time streaming analytics is important when quick response is necessary, such as fault detection or safety-related issues.

Advanced IIoT platforms also leverage machine learning and AI algorithms. In an IoT context, AI and ML can detect unseen anomalies, optimise production processes, and predict future outcomes. Davra users can deploy a trained AI or machine learning model into the platform. We support all runtimes, libraries, and frameworks as long as they can run inside a Docker container.

Security & Compliance

Networked devices, sensors, and machinery are vulnerable to many forms of cyberattack. Data breaches can have severe consequences for any business. As such, strong security and compliance are absolute necessities for an industrial IoT platform.

Some key security features in an IIoT platform include authentication, authorisation, data encryption, network and device security, monitoring, and incident response.

Sectors such as manufacturing, energy, and transportation are often subject to strict regulatory frameworks to ensure the safety, privacy, and reliability of the operation. Compliance is both a legal requirement and essential for maintaining trust among stakeholders and avoiding penalties and reputational damage.

Regulations and certifications the Davra complies with include ISO 9001, ISO 27001 (opens new window), SOC-2, DOD-IL5, and the NIST Cybersecurity Framework.

Robust security and compliance (opens new window) controls offer a competitive advantage to any solutions built on that platform. Inheriting those controls makes your solution more secure, and reduces the likelihood of penalties for non-compliance. Building on a compliant platform also makes it far easier for the solution to be compliant.

Edge

Edge computing plays a crucial role in IIoT platforms. It acts as a bridge between the sensors and machines generating the data and the centralised cloud or data centre. Processing data at the network's edge improves responsiveness, reduces latency, and enhances security.

The edge is located near where data is generated, such as within a factory, on a train or bus, or in a remote field or mine site. This proximity reduces latency by processing data locally without needing to send it to a remote data centre. By processing data locally, edge computing also reduces the load on the network, optimising bandwidth usage and reducing costs.

Devices at the edge must often operate in harsh, unsecured environments with unreliable network coverage. As such, they often have rugged form factors designed to operate autonomously, even when disconnected from the network.

Edge computing can enhance security by processing sensitive information locally and transmitting only aggregated or anonymous data to the cloud. This minimises the risk of data breaches during transit and reduces the attack surface for potential cyber threats.

Conclusions

An Industrial Internet of Things (IoT) platform is a complex system made up of several essential "pillars." From device management to edge computing, these pillars form the backbone of scalable, secure, and efficient IoT applications.

Investing in a platform like Davra's allows you to focus on creating successful applications while we take care of everything else.

Whether it's ensuring reliable connections, managing vast amounts of data, integrating disparate systems, or leveraging advanced analytics, our platform offers a robust foundation for IoT innovation. In addition, our comprehensive security and compliance ecosystem gives our users peace of mind and a competitive edge.

Davra's IoT platform helps organisations unlock the full potential of connected technologies, enabling them to drive growth and innovation.