This article appeared in Electronic Design and has been published here with permission.
What you'll learn:
- What are some of today's major application areas for edge computing?
- The main technical challenges still facing IoT and edge computing.
- How to optimize a Wi-Fi ecosystem for the IoT.
It’s predicted that there will be more than 41 billion IoT devices in use by 2027. This is up from an already staggering 8 billion just two years ago. Why the unbelievable exponential growth? In large part because these devices are turning out to be incredibly useful for businesses, automating and streamlining processes in every industry. However, all of that automation comes with an enormous volume of data, and trying to collect and analyze that data, then transforming it into actionable information, isn’t always easy.
Enter edge-computing (EC) platforms.
These platforms aim to remedy the pain points felt by businesses who are sending all of their IoT data to the cloud. The cloud process can be slow, inefficient, and costly, none of which helps businesses optimize and get ahead.
Edge-computing platforms, or edge analytics, on the other hand, are situated near IoT devices, making it possible for them to collect and analyze data where it originates. This ensures that businesses can use the analytics in near real-time, which is the timeframe you want to be working with when it comes to improving operational efficiency and planning predictive-maintenance upgrades.
If you’re looking to bridge the gap between data and analytics, here are some industry-specific use cases for IoT/EC, challenges to consider, and tips on how to optimize your network to ensure you reap all of the benefits of these technologies.
IoT and Edge-Computing Use Cases
In transportation, both technologies will make self-driving vehicles possible, as cars take in data from the world around them and update controls in real-time. Intelligent road message signs can be updated to provide up-to-the-minute traffic and safety information while toll booths will be able to recognize cars and RFID tags from a distance, raising barriers before cars come to a complete stop. Vehicle-tracking systems will help freight companies monitor distance traveled, fuel consumption, and the status of freight, such as whether or not refrigerated items are at the proper temperature. Real-time tracking of public transportation can help commuters plan trips more efficiently, too.
In healthcare, devices like smart beds monitor patient health in real-time, providing alerts to providers if a patient falls while remote patient-monitoring technology tracks the vital signs of patients, either while they’re in a hospital or after they’ve returned home. Some hospitals and nursing homes also use location-tracking technology to monitor patients with Alzheimer’s.
In finance, edge computing results in faster cybersecurity threat detection. Both IoT and edge technologies contribute to real-time updates on wait times for in-person customers, and constant market updates and analytics for investors and traders will be possible. In addition, voice- and facial-recognition scans can be used to approve secure transaction and we’ll see more stores use beacons for mobile payments, replacing point-of-sale technology.
In manufacturing, the real-time detection of issues with equipment, as well as predictive maintenance alerts, save companies time and money by reducing downtime. Smart assistants can ensure that the correct items have been selected before packing and delivery, and devices can be used to monitor equipment performance and the security of remote sites.
In construction and real estate, EC can be used to support augmented- and virtual-reality (AR and VR) tools that allow decision makers to preview building changes before demolition. Smart-building technologies monitor factors like temperature, lighting, air quality, and security, and sensors can be used to track the number of people that enter and exit certain areas, helping to streamline cleaning and hygiene services.
IoT and Edge Computing Challenges
- Operational: According to the Eclipse Foundation, enterprises’ largest operational challenges when it comes to IoT and edge tech are end-to-end IoT solution monitoring and management; device management; and network, devices, and data security.
- Security: These technologies help unify business processes, but a proliferation of IoT devices also leads to security challenges. For example, many of these devices don’t support WPA2-Enterprise, which is considered the leading option for Wi-Fi network security. Furthermore, different edge devices will have different built-in authentication and security capabilities. To alleviate any cyberattack possibilities, businesses should pursue complete network visibility, and plan to both certify all connected devices before they can connect and determine how to isolate or segment different groups of devices.
- Privacy: Companies must ensure the privacy of individuals, as well as that of the business, when collecting data. With more and more IoT devices entering the scene, some of which may connect to individual laptops or tablets, or even people themselves, companies must make sure that their privacy practices evolve equally as fast as device adoption.
- Geographic: While edge-computing platforms can be beneficial for remote sites that would otherwise spend lots of time and money sending data back and forth to distant cloud systems, companies might find managing these systems challenging if there aren’t IT teams onsite, and if there’s no remote way to monitor the platform.
- Potential loss of data: Edge platforms can discard any data considered useless, rather than taking the time and energy to send all processed data to a cloud storage center. This could, in the long run, mean that a company doesn’t have access to data that has suddenly moved from useless to useful.
Optimizing a Network for IoT and Edge
Without an optimized network, you will never see the best ROI from IoT and edge platforms. That’s because these platforms depend on a constant influx of data from IoT devices if they are to provide accurate, real-time analytics. And without optimized Wi-Fi, devices can’t reliably gather and send that data.
So, how to optimize the Wi-Fi ecosystem? Since most company networks are fast-paced and complex, with hundreds or thousands of connected devices, network optimization requires complete visibility with AI-driven analysis, remote monitoring, and historical data. These capabilities additionally help to address many of the challenges shared above. Here’s how:
Complete Visibility and Proactive Alerts
IT teams can’t optimize the network if they don’t know exactly what’s on the network and how the network is being used. Complete visibility removes the possibility of network mysteries and improves network security.
Ideally, IT should be able to see every connected device, whether connected wirelessly or wired; all back-end and front-end infrastructure; any non-Wi-Fi devices like microwaves that can impact network performance; and any nearby networks sharing the same airspace. To increase security, this complete visibility can include automatic alerts when unknown or unauthorized devices connect to the network.
For the proactive feature, complete visibility platforms must include AI-based analytics. After all, to upgrade the network optimization process with the greatest efficiency, IT needs actionable insights into device behavior, not simply a map of connected devices. With AI analytics, monitoring platforms are now empowered to learn to recognize normal and abnormal network behavior. When abnormal behavior occurs, the platform can proactively alert IT, often before end users are ever affected, reducing network and operational downtime.
Complete visibility and proactive responses address the following IoT/EC challenges:
- Operational: With complete visibility, IT has up-to-date information on all connected devices, making device management much simpler. Devices and device actions also are monitored in real-time, with data captured in the RF environment in which it’s sent, making this capability ideal to address end-to-end monitoring and management concerns.
- Security: Proactive alerts into abnormal behavior allow IT to address and resolve any security concerns much quicker compared to situations when teams must wait to be alerted by reactive solutions or end users. Complete visibility means that any unauthorized or unknown devices that connect to the network are spotted immediately.
Remote Monitoring
As we all know, there are times when IT teams can’t travel onsite. This travel delay might last hours or days, but either way, the delay can mean detrimental costs to a business’s productivity. To combat this, companies should have the ability to remotely monitor and troubleshoot Wi-Fi networks.
This allows IT to resolve problems from any location at any time. It also enables IT to work from one central location, rather than requiring them to stand in busy hallways or offices to capture packet data and identify the root cause of issues.
Here’s how this addresses common IoT/EC challenges:
- Operational: Teams can monitor and manage device health and behavior from any location.
- Security: If there are any security issues, IT can resolve them much faster than if they were required to travel on-site.
- Geographic: While teams must be on-site to install devices, they can then manage and troubleshoot them from any location.
Historical Data
Without historical data, decision makers lose insight into the long-term health and performance trends that affect network behavior. For example, historical data answers questions such as:
- How has network utilization changed?
- How has network demand and capacity changed?
- How are APs performing? (Performance might be slowly degrading even if there are no real-time issues.)
- How did the noise floor change throughout the year?
With answers to these questions and others, administrators can design cost-effective and personalized plans for network upgrades and updates, future-proofing the network based on its specific needs, rather than responding to general market trends.
This helps resolve these IoT/edge challenges:
- Operational: Historical data helps IT monitor devices’ overall health and performance.
- Lost data: If the platform automatically saves historical analytics, IT can “time travel,” reviewing past data even when the exact network conditions no longer exist.
While you can search out individual solutions for complete visibility, proactive alerts, remote monitoring, and historical data, one of the most efficient ways to attain these capabilities is to work with an all-in-one Wi-Fi automation platform. These platforms automate the monitoring and analytics process, performing real-time computations on thousands of data packets a second, and providing IT with actionable, proactive alerts.
Optimize Next-Generation Networks
With IoT and edge adoption only set to increase, companies need to plan now to optimize and future-proof their networks to support these devices and be able to fully benefit from their analytical insights. Look for a way to bring the above capabilities to your Wi-Fi and proactively shore it up so that optimization becomes the norm.