Smart City AI: NLP and Robotics in Action

colorful robots
Posted by Tisha Hulburd on Jun 24, 2020 9:48:57 AM
Tisha Hulburd

By now we’re accustomed to meeting natural language processing, or NLP, in our daily routine. Personal assistants like Siri and Alexa and voice response systems greeting us when we call a company’s customer service line are just some of the many ways NLP is used in an attempt to remove friction from task completion. NLP enables computers to read text, hear speech and search for the key phrase in large datasets to return answers to questions spoken or typed into devices. NLP is an attempt to make the way computers interact with humans, to make the interchange between the question and the answer, correspond to the way humans naturally query, or form questions. As SAS explains, “NLP is the branch of AI that enables computers to understand interpret and manipulate human language.” But NLP is only one subset of the incredible growth of use cases for artificial intelligence, or AI, including at the local government level.

AI: The Rise of Technology in Government

AI technology has been widely used with much success in the private sector and is on a tremendous upward growth curve. U.S. businesses are projected to spend $36 billion on AI by 2025.

AI is the foundation of smart city platforms as it brings significant data analysis capability to the large amounts of data currently stored in multiple legacy city systems and generated by newly connected city devices, including smart sensors that monitor traffic and utility sensors that monitor water and wastewater systems, for example. AI can turn the data collected into not just reports, but actionable insights.

Writing for govtech.com, Tod Newcome noted “government has become quite bullish on real-world applications of AI that can find ways to improve the environment, make public spaces safer and, most importantly, strip out the mundane, manual work that clogs up government operations.” 

And cities will need the help. Cities are expecting massive growth in the coming years; urbanization projections are looking at 2.5 billion more people living in cities. With that kind of growth, city government can no longer afford to lag behind in the digital landscape. Connecting, engaging and fulfilling of services between city and government will need to become increasingly digitized to keep up with rising demand while budgets remain tight, or in the near term, face deep cuts. Digital experiences, delivered through a customized city mobile app, can be made more efficient when complemented by AI technologies, including NLP, image recognition and robotics, and these efficiencies translate to better experiences and reduced costs. In addition to larger smart city applications that cover utilities and traffic management, there are many opportunities for AI to improve citizen engagement and city service delivery.

State and local government house myriad processes that require a great deal of human interaction to complete manual, repetitive tasks, the kind that ‘clog up government operations.’ Automating these processes could divert human energy to other tasks that require more thoughtful interaction, reducing costs while improving outcomes.

“There are many use cases where this type of AI technology makes sense for cities,” said Steve Denney, Co-Founder and CTO at CityFront Innovations, a leading provider of AI technology for mobile city applications. “For example, think about the process by which a citizen gets a permit. Maybe they go online and try to find the form, which can be quite frustrating experience in itself. So they end up calling city hall, trying to navigate the various departments on the phone to find the right person to ask about the form. Or, they may end up going down to city hall to get the form and get it submitted, that is, if they happen to have access to difficult to find information, like their lot size or tax parcel ID number.”

Processes like these are good candidates for AI technology. Said Antony Edwards, COO at Eggplant Software, “Put simply, the role of RPA is to automate repetitive tasks that were previously handled by humans. The software is programmed to do repetitive tasks across applications and systems. The software is taught a workflow with multiple steps and applications.”

Following the city-focused use case of filing a permit application is one example of various aspects of AI working together to produce a more efficient process. NLP serves to help a citizen find the right form, and robotics comes in to properly complete and submit the form through automation. A citizen could, for example, speak in to their smart device, “I need a permit to remodel my house.” An NLP engine trained to the city’s specific permit and other document systems returns the correct form and robotics takes over, interfacing directly with other city systems to find and return the correct information, reducing errors and the need for staff mitigation. Appropriate fees and disclosures can augment a guided process to complete the cycle.

That means fewer phone calls and fewer citizen visits to city hall. Cities who process several thousand permits annually can save hundreds to thousands of hours each year on permit processing, and citizens will experience less friction and frustration in completing necessary paperwork.

“Use of AI in these types of cases can free up city personnel to focus on other tasks that require more thoughtful interaction,” said Denney.

But AI can bring additional benefits to the process: collecting data at all touchpoints can detect trends and bottlenecks in the process, highlighting opportunities for improvement. For example, permit applications that are returned at a specific point in the process at a higher rate may reveal an opportunity for improvement that can reduce or remove the bottleneck: perhaps there is an ambiguous question, or a connection to another city system that is not optimized. Spotting this trend may be difficult when a team is processing thousands of paper applications manually.

Want to see NLP and robotics in action? Check out this brief video for a quick demo. It’s pretty cool.

About CityFront Innovations: About CityFront Innovations: CityFront partners with cities, municipalities and community organizations to deliver the first smart city integration platform, powering an artificially intelligent (AI) citizen engagement mobile app that enables citizens to engage with the city intuitively and intelligently. To learn more, contact us.

Topics: smart city, AI, natural language processing