IoT Can Make Return to Workplace Easier, but Smarter Networks Required

IoT Can Make Return to Workplace Easier, but Smarter Networks Required

We are fast approaching a time when everything will be connected, because the internet of things (IoT) is now mainstream. Businesses and consumers are connecting traditionally unconnected “things” at an unprecedented rate. This includes everything from security cameras, to medical devices, to point-of-sale devices to building automation systems—and the list goes on. 

All in all, my research forecasts there will be 80 billion connected devices in 2025, more than double the 30 billion today. One of the interesting aspects of IoT is that all these internet-connected devices are continuously collecting and transferring data over networks without human involvement. Harnessing the intelligence from the IoT generated data can lead to interesting insights that can help transform a business. 

The pandemic has accelerated the adoption of IoT 

COVID-19 further heightened the use cases for IoT. Things such as robotics, drones and sensors are helping certain industries enable contactless interactions. Robots are being used in hospitality for food delivery and housekeeping. Some hospitals have even deployed video-enabled remote doctor robots to limit physical contact with sick patients. In other instances, drones are bringing supplies to communities affected by the pandemic. IoT surveillance systems are also growing in popularity for protecting property and assets.

While overall spending took a hit during COVID-19, the IoT market is expected to rebound in 2021. Extreme Networks provided a pragmatic outlook for the future of IoT during a recent webinar, IoT & Network Infrastructure Workshop: In a World of Robotics, AI & ML. IoT will be a key driver for businesses going through digital transformation. Many of the investments will be in insurance, education, manufacturing, and notably, health care. In fact, IoT health applications—such as air quality sensors and remote patient monitoring systems—are expected to surge. 

IoT project failure rate is high 

Whether organizations succeed in their IoT deployments is a different story. In the webinar, Extreme highlights that fewer than half of IoT projects make it past the proof-of-concept stage. This is consistent with the research I have done in IoT. In fact, as IoT devices become broader and involve a broader set of connected endpoints, the percentage of projects that are not completed has risen. 

This is because IoT is a complex ecosystem of physical devices that transmit data to gateways, which must translate IoT specific protocols to something the network can understand. The data must then be aggregated from all the connected endpoints. Lastly, it must be stored in a data center or in the cloud, then managed and analyzed in depth.

Streamlining and processing key data is an important part of any IoT deployment, as it allows organizations to gain true business insights. Extracting valuable insights from IoT data requires artificial intelligence (AI) and machine learning (ML) tools. Such tools can not only analyze massive amounts of data from tens of thousands of connected devices and sensors, but also detect anomalies and security threats. 

IoT security remains a significant barrier 

One of the biggest barriers to IoT deployments is security. Every IoT device connected to the network increases the attack surface, potentially providing intruders with an entry point into the network. In addition to securing IoT devices, it’s essential that data is encrypted both in transit and in the data center or the cloud. 

However, it’s difficult to trace every device connected to the enterprise network—a problem known as shadow IoT—and it’s making IoT devices more vulnerable to ransomware. Hospitals are widely targeted in this type of attack. But ransomware has been known to strike industrial control systems and even critical infrastructure in some IoT deployments. The IoT cybersecurity landscape is constantly changing and is expected to grow in complexity as more devices connect to enterprise networks.

ExtremeCloud IQ simplifies IoT Security 

Businesses can ensure IoT network security by implementing tools such as ExtremeCloud IQ, which identifies all connected devices and their authentication details. Once there is a complete view of the devices connecting to the network, ExtremeCloud IQ applies security policies and access control for each device category. For example, medical-monitoring equipment would be deemed as business critical, while a printer is non-critical. 

Businesses should also consider segmenting their network, so IoT devices are separated from each other and the main IT network. The process can be complicated, since placing IoT devices in separate virtual local area networks (VLANs) requires manual configuration. ExtremeCloud IQ automates this process by isolating devices through secure segments, both in wired and wireless networks. It also authenticates devices and control access to the enterprise network with a built-in intrusion protection system.

Visibility is key; you can’t secure what you can’t see 

The last component is adding visibility and intelligence to connected devices and network traffic using AI and ML-driven insights. On average, it takes a company a month or longer to discover a breach. With advanced tools, businesses can perform detailed packet analysis to detect breaches faster. ExtremeCloud IQ, for instance, collects and analyzes more than 300 statistics per device per minute. So if a breach is attempted, network administrators can determine when it happened and how serious it is.

In summary, IoT will have a major impact on how networks are designed. Networks of the future will have to be more agile and intelligent to analyze all the data generated by connected devices. By investing in AI and ML-based tools, businesses can get a better handle on their IoT deployments by making predictions faster with greater accuracy.

Zeus Kerravala is an eWEEK regular contributor and the founder and principal analyst with ZK Research. He spent 10 years at Yankee Group and prior to that held a number of corporate IT positions.

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