What agencies need to know about the Internet of Things

By Dave Shuman 

The opportunity for Internet of Things (IoT) adoption in the public sector is vast. Agencies have innumerable ways to leverage IoT to diminish costs and boost productivity, ultimately improving services and safety for constituents. A few ways in which this is materializing include:

• Vehicle sensors for public buses, government fleet, and first responders to improve vehicle routing, fleet health, fuel consumption and response times through the analysis of telematics data 

• Data from ankle monitors to improve prisoner and parolee rehabilitation and deter recidivism 

• Data from body-worn cameras and the ubiquitous network of cameras and video sources on which law enforcement rely to improve forensic capabilities 

• A number of smart cities and connected infrastructure use cases including smart parking, smart lighting, smart traffic, smart garbage pick ups to name a few. 

Such examples capture what can be done at the state and local level to improve constituent services, government efficiency and public safety, and offer just a few ways that the government can utilize IoT. From smart cities working to improve infrastructure and energy efficiencies, to localized sensors improving first responders’ ability to respond to natural disasters, the options are endless when it comes to ways the government can leverage IoT. 

But there are important risk factors that must be considered when evaluating how to fully leverage IoT benefits. Here are four considerations the public sector should keep in mind as it connects more and more devices.
 

Cybersecurity needed to protect devices 

Strong cybersecurity hygiene includes modernizing legacy technology and developing a smart workforce that is well-trained on how risks are perceived and managed. To support the need for enhanced vigilance, a group of senators introduced legislation in August that would use the government’s buying power to establish minimum security levels that IoT devices sold to the United States will need to have. This includes patching devices with security updates and prohibiting tech companies from hardcoding passwords into devices sold to the federal government. 

Data governance considerations are fluid

Most IT organizations, both public and private, don’t understand that data governance requirements change as technology is connected. Different processing frameworks and combinations of data require different data governance considerations. Agencies should be sure to maintain fair use of data.

Tools are needed for extracting, transmitting, processing data

IoT devices generate a vast array of data, but making sense of the data from millions of connected devices isn’t possible without a modern platform for machine learning and analytics in place. Without the ability to derive actionable insight, the data generated from IoT devices is moot. The volume, velocity and variety of data generated through even a single device is too much for traditional data analytics platforms to manage in real-time. Agencies must modernize in order to truly maximize the value of IoT-generated data. 

Look to the private sector for talent and lessons learned 

Agencies should look at IoT device vulnerabilities impacting the private sector when charting a course forward and be open to collaborate with businesses on best practices and lessons learned. In addition, an IT talent shortage is something that has plagued many facets of the public sector, and it is no different when it comes to IoT-centric jobs. Agencies need employees well versed in IoT as well as the data generated by IoT devices. Because IoT adoption in the private sector is more advanced, its workers are familiar with IoT best practices and thus offer an attractive recruitment pool for government. 

IoT holds infinite possibilities for the public sector. Yet with possibilities also comes increased risks and considerations that must be taken into account in order to fully maximize the benefits.

Dave Shuman serves as industry leader of IoT and manufacturing at Cloudera, a machine learning and advanced analytics platform provider.

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