Edge Computing Is the Key to Deriving Value from IoT Data
State and local governments are rapidly deploying Internet of Things (IoT) devices to gather real-time data and automatically control systems. Light poles can be used to deploy sensors that monitor weather conditions and air quality, as well as video surveillance cameras that capture suspicious activity. Smart traffic lights employ sensors to route traffic more efficiently than traditional timers. Sensors are also being used in fleet management systems to monitor fuel consumption, maintenance requirements and driving patterns.
This data can be used to drive analytics applications that can increase efficiency and enhance decision-making. Government agencies can reduce costs, improve safety, and better track, manage and maintain assets to minimize unplanned downtime.
Not surprisingly, the public sector is rapidly embracing IoT technologies. By some estimates, pubic sector IoT initiates are worth more than $30 billion and will see a compound annual growth rate of 20 percent through 2021.
However, IoT implementations are not without challenges. Government agencies need a robust network infrastructure that can scale to support growing numbers of devices. They need automated processes for onboarding devices and ensuring they are secure. Most of all, they need to have adequate compute and storage resources to handle the onslaught of data.
Why Edge Computing
Managing large volumes of data generated by IoT devices, and analyzing that data in real time to uncover insights that deliver value, is no small undertaking. Simply collecting data from an endpoint and sending all of it to the data center or cloud for processing is inefficient. It also creates latency that limits the value of the data.
The concept of “edge computing” has arisen to address this challenge. By moving compute and storage resources to the edge of the network, close to the IoT device, data can be processed at the source before it’s sent to the data center or cloud.
Edge computing is critical when real-time analysis is required, as with autonomous vehicles and many safety systems. It can also benefit more complex analytics by filtering data at the source to reduce the strain on the network. Let’s say, for example, a city installs video cameras to get an accurate count of vehicles at a particular intersection. It’s far more efficient to implement video analytics at the edge than to transmit hours of raw footage to the data center for analysis.
The Role of the IoT Gateway
Of course, edge computing creates a new level of complexity. Government agencies must be prepared to manage and control complex systems using multiple connection protocols that are dispersed across a wide geographic. That’s where the IoT gateway comes in.
An IoT gateway is device that aggregates connectivity for multiple devices at the edge. Best-in-class IoT gateways feature security controls that help prevent IoT devices from being used in a botnet. Some can also be used to filter and process data directly from sensors.
Cisco offers IoT gateways for a wide range of applications, including ruggedized components that are built to withstand the harshest environments. They provide zero-touch provisioning, support both cellular wireless and Wi-Fi data services, and include integrated security features. The Cisco Kinetic platform gives you the tools you need to manage IoT gateways remotely, and to filter and transform sensor data before it’s securely transmitted to the data center or cloud.
Smart government applications are expected to generate a “data tsunami” of more than 16 trillion gigabytes every year. Cerium’s engineers can help you evaluate Cisco’s edge networking tools and develop a strategy for harnessing the power of IoT data.
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