Crime is a pressing safety issue in America. Total violent crimes surged by almost 10% in large American cities between 2020 and 2021, continuing a decade-long trend of escalating violent crime rates. This upward trajectory raises concerns about civilians’ safety, who face an increased risk of robbery, assault, and even homicide. As a result, jurisdictions are tasked with prioritizing public safety measures to better protect and serve the public.

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One of the challenges in addressing crime rates is the difficulty faced by police departments and their emergency communications centers in manually sifting through resulting data and tips. Not to mention the difficulty these organizations have filling vacant positions left by retiring officers, staff leaving the profession, or attracting fresh recruits. As a result, this has led to longer response times for emergencies, putting people’s lives at risk.

Eleven minutes is the average response time; however, given the current situation, it takes longer in many states. While staff shortages may be one part of the problem, more data coming in from surveillance cameras, traffic sensors, and IoT devices, to name a few, are causing staff to become overwhelmed and more likely to miss relevant information.

There are ways for agencies to step up their game, especially when giving these day-to-day heroes support so they can maintain their focus on serving the community and identifying situations that need their attention faster than ever before.

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It begins with investing in AI.

By amplifying technology with AI, departments can better safeguard the public, alleviate the significant stress first responders grapple with day in and day out, and do their jobs more efficiently. Furthermore, leveraging a collaborative ecosystem augmented with AI can transform data and processes enabling agencies across a city to detect, decide, and act together.

Technology Is Your Friend; Assistive AI Is Your Partner

Technology and law enforcement agencies have long worked hand-in-hand together. For agencies today, it is a significant challenge to harness all disparate data flowing into their organizations. AI helps to sort through real-time data from incidents, IoT devices, and other sources. Because the AI is assistive, it mines the data and then alerts staff to trends and anomalies, leaving the decision-making up to humans.

It can provide real-time insights as complex emergencies unfold. Assistive AI can play a crucial role in supporting the employees working in dispatch centers. By automating tedious research tasks, AI systems allow personnel to identify situations that require immediate attention more efficiently, thus enabling them to perform better at their jobs, ensuring no response time is delayed.

Looking ahead, the potential for AI in not just law enforcement, but the public safety space as a whole, is vast. Now, AI has tremendous potential to digitally transform municipalities and break down the data silos that have hampered the collaboration necessary for disparate public safety agencies to work better together for the public good.

Faster response times can mean the difference between life and death for people.

Ready to make every second count?

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[To share your insights with us, please write to sghosh@martechseries.com]

The post Evolve Your AI Strategy For Better Emergency Response Times appeared first on AiThority.

The term “smart city” is often used to describe Internet of Things (IoT)-focused projects. And for good reason. According to the Identity Management Institute, the number of active IoT devices will surpass 25.4 billion by 2030. Millions of these devices monitor assets, infrastructure and the flow of people and goods in cities.

But it’s also true that implementing a smart city strategy is about more than installing connected devices for specific digital projects. It’s also about the collaboration required between a variety of municipal agencies and organizations to break down silos that prevent the various data streams and people from coming together. It’s in this coming together that smart cities become more about outcomes than devices.

It Starts with Integration for Smart Cities

Integration begins by effectively sharing data from diverse assets, incidents, resources, devices and feeds. It continues by linking people and information from different city departments, service providers, community organizations and regional partners to coordinate action and solve common and uncommon problems together.

The ability to transform data and processes into a collaborative ecosystem enables city departments to detect, decide and act together – making smart city management even smarter. While enterprise technology barriers, such as integrating disparate critical systems, IoT devices and applications, as well as human barriers, such as data ownership and exchange standards, can hamper such collaboration efforts, it doesn’t have to be that way – far from it.

For example, municipal leaders in Manaus, Brazil, wanted to improve the quality of life for 2.2 million residents by more effectively predicting and responding to citizen needs through better cooperation between public organizations. In 2021, Manaus established the City Cooperation Center, which houses public safety, disaster management, transportation and other agencies. In addition to connecting the different organizations and their incident data, the cooperation center also integrates data from surveillance systems, weather stations, public applications and sensors located across the city. With connected data and coordinated workflows, these agencies can identify and resolve problems and emergencies faster than ever before.

AI Adds Insight

Key to this and similar efforts, from real-time crime centers to transportation and utility operations centers, is the ability to quickly analyze and make decisions based on large volumes of diverse data. That’s where AI can help. When incorporated into a real-time operational context and embedded into an operational system like computer-aided dispatch and other incident management and monitoring applications, this form of assistive AI can provide rapid decision support by augmenting human judgment and intuition.

Assistive AI helps organizations make better decisions by sorting through data from incidents, IoT devices and other sources in real-time. Because the AI is assistive, it mines the data and then alerts staff to trends and anomalies but leaves the decision-making up to humans.

For example, it can provide real-time insights as complex emergencies unfold. Because manually monitoring videos, alarms, and common operating pictures (COPs) is often focused on individual events, it is not always reliable. Assistive AI mines the information as it comes in from a variety of systems, giving staff immediate access to intelligence. As a result, public safety authorities can significantly change workflows and operations to better meet the situation at hand, ultimately reducing the impact on available resources and the community.

Manaus’s vision for improving incident management includes the use of AI alongside its operational systems for real-time detection, analysis and coordinated response, from public safety emergencies to parking violations and infrastructure repairs.

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Looking Ahead: Intelligent Collaboration 

With Manaus as an example, cities are able to integrate, modernize and digitize city planning and operations to make their smart city goals a reality. That’s possible not only through more and better data from IoT devices, but also through more effective and efficient methods of sorting through and acting on that data.

Municipalities can achieve their full potential for digital transformation by thinking beyond sensor investments and considering the value that integration, real-time analysis and cross-city collaboration can bring to smart city initiatives. Collecting data is only the first step.

What you do with it matters more. And, results require more collaboration and better decision-making.

[To share your insights with us, please write to sghosh@martechseries.com]

The post Making Connections for Smart Cities appeared first on AiThority.