IoT & Automation

While the progress towards smarter building infrastructure is impressive, it is important to remember that it is not without risk. Unfortunately, the diverse range of IoT systems within smart buildings are still running old, unpatched software and frequently communicate using nonstandard protocols. This makes malicious activity and potential security threats much harder to detect. Moving forward, it is imperative that the building industry and developers strictly deploy smart systems that have security built in from the start. When it comes to connectivity, the implementation of VPNs is critical for protecting smart buildings and ensuring device data is kept private and secure.

Organizations around the world are investing enormous amounts of resources in pushing computing to edge devices.   There are use cases across most industries like self driving cars, smart grids, healthcare, and many more.   These solutions are beginning to take on similar architectural patterns as they evolve from concept to reality.  The data value chain is going to move directly to the edge over the course of the next few years as more and more organizations see the need for real-time analytics directly on an intelligent edge.    

Developments in IIoT data protection are currently failing to keep up with the rapid rate of innovation and demand. The top three challenges for IT professionals are IIoT integration, migration/installation risks and privacy concerns.  Built-in security is the answer to establishing a trusted standard of IIoT security. Centrally managed VPN software provides vital data encryption for the many thousands of remote connection points that make up an IIoT environment. In combination with built-in security features and processes, VPNs provide robust protection for maintaining the privacy and integrity of highly sensitive IIoT data.

There is a bounty of business use cases from which the business can choose in order to monetize their IOT efforts. The best approach is to build out your IOT Business Strategy with one use case at a time. In this manner, not only do you incrementally build out your IOT analytic, data, technology and architecture capabilities, but this enables the organization to build upon the work of previous use cases – to capture, share and refine the IOT data and analytic assets that are key drivers to IOT monetization.

Enterprises are experiencing a rapid evolution in technology that is challenging traditional security systems and infrastructures. The arrival of business-oriented IoT devices creates even more demand for secure connectivity. To avoid security breaches, IT departments must secure connections for more users and devices than ever before. Providing encryption for the communications of many thousands of devices, virtual private networks (VPNs)are a tried-and-tested way to ensure sensitive company information remains secure and private. When deploying VPNs for a multitude of devices, a large-scale management solution is essential that can greatly enhance the productivity of IT departments and keep corporate networks secure.

Some of the fastest applications that will be dominated by IoT are healthcare devices, wearable devices to enhance currently restricted capabilities, energy saving devices and smart devices for inter-connectivity in real time use. We will soon have smart homes, connected mobility (transportation), smart cities, and even smart forest zones and marine life to create better air, water and live a healthier life. We need devices that will bridge the gap between physical and digital world to improve the quality and productivity of life, society and support the eco-system. 

What many businesses forget is that IoT devices are not typically secure. In fact, they are designed to remain cheap and lightweight, which makes them difficult to manage once they are connected to the network. There are several reasons why IoT devices create a visibility challenge. As device manufacturers aren’t required by consumer protection laws to integrate security features, now is the time for enterprises to focus on gaining complete IoT visibility. It starts with understanding the inventory of connected devices and ends with segmenting those devices into areas of the network with limited access according to their needs.

Adoption of IoT is going to continue to drive an adoption of hybrid cloud. As a result, the solution to these problems cannot simply be providing a managed service for an incredibly complex product. The product itself needs to be simple and easy to use, yet highly scalable, so that it can be deployed and managed directly on the edge and in the cloud with the same level of effort and skill set. In order to continue to drive and support innovation, the data management industry needs to design and build the traditional big data architectures required to consume IoT data and transform that data into valuable insights, identify patterns and make it actionable.

Today, we are siloed in how we think about IoT. We develop solutions for the sake of technology and continue to think in small incremental steps about the data we are collecting. It’s relatively easy and cheap to deploy a connected sensor and collect data, but it’s the easy way out and everyone is doing it. The industry is missing a critical link: the marketplace for IoT to use the data collectively and build an ecosystem for distributed monetization of data. This is where AI comes in. The convergence of AI and IoT can change this by creating a connected system of things that can be used in everyday life. 

While IoT has many advantages, enterprises need to overcome some important problems in cloud computing to fully gain from these potential advantages. It’s a known fact that IoT and the cloud are impossible to separate—but only about a third of the data collected by the growing army of sensors is analyzed at source. While IoT has many advantages, enterprises need to overcome some important problems in cloud computing to fully gain from these potential advantages. Fog computing facilitates the operations of computing, storage, and networking services between end devices and cloud computing data centers. 

Most companies get caught up in the first few stages of product development and miss out by not planning for Stage 4 sources of value. The challenge for manufacturers aiming to profit from IoT opportunities is to manage their product development road-map strategically. They have to anticipate solution “mash-ups” and data from different ‘vertical’ silos or third-party sources. The supply-side of the IoT market faces its own challenges. Basic connectivity will be commoditised once technology choices are simplified. By then, network and platform interoperability will drive value through new business models based on shared resources and data assets.