The Future of Smart Cities and Local Governments

From aqueducts to grid plans, cities have been both the ultimate catalysts and ultimate tests for technological innovation. Yet, as new technologies emerge, their implementation into communities requires intentionality from every stakeholder, including municipal governments, law enforcement officials, and citizens. Despite its novelty, AI is no different. Accurately informed stakeholders can be the key to successful implementation, so let's dive in.

How Can AI help Government and Cities?

AI can help governments and city officials focus on what's most important - their citizens. With the capabilities of AI systems, we will see more efficient work for cities that invest in this technology.

With Artificial Intelligence (AI), Video Analytics, and Machine Learning, cities/counties can increase safety and security efficiency to achieve the Smart City vision. AI helps public agencies reduce costs by streamlining processes while increasing accuracy when performing tasks such as remotely monitoring events, analyzing data from surveillance cameras, investigating accidents, conducting inspections, and responding to emergencies.

Video analytics detects events that occur across the camera field of view (FOV) by extracting information from live video and video surveillance footage, enabling public safety agencies to act more swiftly - a critical factor in emergency response. In addition, cities and counties can now improve services with Video Analytics, Artificial Intelligence, Machine Learning (AI/ML), and mobile apps for citizen engagement.

These technologies are not new to public agencies that use them in their daily workflows. For example, in 2013, the FBI used Briefcam Video Synopsis to reconstruct the Boston Marathon bombings and identified the two suspects related to the bombing attack on record time.

Video Analytics enables public safety agencies to carry out procedures in the field with mobile apps and conduct sophisticated searches for objects, people, and text in the archived video. In addition, machine learning is used to interpret Big Data from various sources - such as police body-worn cameras, law enforcement attendance records, and 911 calls that identify victims of violence or high-risk situations. Moreover, Artificial Intelligence, Video Analytics, and Machine Learning can understand interactions between objects and people, enabling cities/counties to improve their safety and security strategies.

Our Changing Cities

The Covid19 Pandemic has entirely shifted city life. Cities were usually characterized by their crowded and bustling nature; we now live in cities defined by distance. AI cameras and occupancy monitoring systems can help ensure physical distancing in spaces by measuring the distance between occupants and tracking the number of people entering or leaving an area. These cameras can even detect whether or not someone is wearing a face mask, alerting you to any potential violations. These systems can be precious in public indoor spaces such as museums or government buildings. As public health guidelines shift daily, AI systems can take the stress of monitoring your areas for physical distancing and mask compliance. 

The pandemic has also transformed how we move around in cities, with some trading out public transportation for a car or others foregoing a commute altogether. So whether you have seen an increase or decrease in traffic due to the pandemic, AI systems can help you monitor and mitigate these impacts. 

Gainesville, Florida, is a prime example, where researchers from the University of Florida Transportation Institute fused a variety of data streams to identify high-risk intersections. Similarly, the City of Austin implemented a pilot program that utilizes the technology to track changes in traffic throughout the pandemic and optimize hundreds of traffic signals throughout the city accordingly. They have also implemented bike stops that use object classification technology to detect bikers and alert them to the next green light.

Urban Planners and Smart Cities

The urban planning process is complex and requires an understanding of the patterns and issues within a specific municipality. Using data from video analytics, planners can make informed decisions to ensure project success with tangible results, including even distribution of pedestrian traffic along sidewalks, resolving drainage problems in certain areas during heavy rainfalls. In addition, cameras can monitor the activity of the public spaces to understand where people are going, how long they stay there, and whether people return to specific locations regularly. 

Urban planners could use video content analysis in many ways for planning purposes, including identifying the number of people who pass through different locations throughout each day. This information can be helpful when deciding where to install services like street lights or bus stops. For example, a camera on a pole could tell an operator how many pedestrians cross a street each day at a particular time. Using that information could then determine the optimal placement of a new bus stop. In addition, planners can use analytics to identify areas with high rates of crime and traffic accidents- analyzing the specific times and days these activities occur to focus their efforts on those locations. 

Trained algorithms can detect unsafe traffic conditions in certain areas, such as speeding vehicles or icy roads. In the case of hazardous weather conditions, automated real-time signs can warn drivers and encourage increased caution. 

However, local governments still have some challenges to overcome when implementing these technologies out on the streets. According to a recent article from CIO magazine, "a constant struggle for IT is integrating new tools with legacy ones." As technologies for video analytics and big data mature, a thorough examination will be required to ensure the integration is as effective as it should be. In addition, all the systems and IoT devices should communicate between them, creating a seamless monitoring system for all government stakeholders. In summary, a single unified platform would enable the urban planning teams to visualize the data they need to do their job.

Final Thoughts

As new technologies emerge, they require intentionality from every stakeholder. Accurately informed stakeholders can be the key to a successful implementation of these novelties.

Ultimately, each of these technologies should receive input from community members before successful implementation, but informed officials and the informed public are the first steps to that community engagement process. Then, as these technologies continue to grow and change, we can capitalize on how they help keep our communities safe while continually striving for a better quality of life.