Smart Cities Technology and Data

The Atlanta City Council unanimously voted on Monday to establish an artificial intelligence commission to explore how the city can incorporate AI into its operations. The commission will convene at least once a month starting no later than February 2025 and will produce a report by February 2026 detailing opportunities for using AI in city government, including potential benefits and challenges. The group will comprise 13 individuals, including Atlanta’s chief information officer, Georgia’s chief digital and AI officer, experts from the state’s universities and multiple members appointed by the city’s mayor and council members from each district.

Although the concept of AI has been around since the 1950s, it has in recent years become more popular due to the large amount of data available, advanced algorithms and computational improvements, according to the Atlanta City Council resolution to form an AI commission. Cities can use AI for applications such as optimizing traffic flow, reducing energy consumption and streamlining administrative tasks, said National League of Cities CEO and Executive Director Clarence Anthony in a November report on municipal AI use published by NLC and Google.

Atlanta is already leveraging some AI-driven technologies. After two water main breaks this summer, officials said the city would pilot AI-enhanced devices that can detect future leaks before they intensify, according to Atlanta News First. 

The city’s newly approved commission reflects the attitude of many local officials and technology experts in the U.S.: Embrace the opportunities of AI, but proceed with caution. 

“With intentional use of AI, city leaders can reduce repetitive tasks and make government operations more efficient, enabling time and resources to be invested back into communities to address resident needs,” Rochelle Haynes, managing director of Bloomberg Philanthropies What Works Cities Certification program, wrote in a public letter to city leaders earlier this year. Among the advice Haynes offered was for cities to create clear guidelines for staff on how to use AI tools responsibly.

City leaders don’t need artificial intelligence-driven technologies to tell them they have a climate change problem, at least in the eyes of Rohit Aggarwala, New York City’s chief climate officer. 

“We don't need AI or big data to tell us with much greater detail how screwed we are as a city or as a planet,” Aggarwala said at last week’s Urban Tech Summit held at Cornell Tech’s Roosevelt Island campus in New York City. 

Technology developers should instead focus on solving “the real problems that we face” in city government, which include engineering, project coordination and funding hurdles, said Aggarwala, who also serves as commissioner of the city’s Department of Environmental Protection.

Aggarwala detailed some of these “real problems” in his remarks. For example, New York City’s building decarbonization law, Local Law 97, is challenged by the multi-billion dollar price tag of retrofitting the city’s buildings and the poor management of many buildings.

“We've got a lot of bad management in a lot of our buildings, and we are asking them to do something that's really difficult and really ambitious,” Aggarwala said. “Right now, we're doing it in the face of interest rates that are really high.”

He also pointed to the engineering hurdles the city faced during work on the Champlain Hudson Power Express, a transmission project that will bring Canadian-generated clean energy to New York. The project developer’s initial design for infrastructure in the city was “absolutely unacceptable,” Aggarwala said, because it interfered with critical sewer infrastructure in the borough of Queens. The conflict underscores how the complexity and cost of doing underground construction in New York City can hold back the renewable energy transition, Aggarwala said.

Challenges like these are the “cutting-edge areas” for potential AI applications, Aggarwala explained.

“If you want to have AI address climate, I need to ask you to help it make government work better,” Aggarwala told the audience. “Particularly in those areas where government is already trying to address things, but it is not in the policy, it is not even necessarily in the money. It is in the way we do things.”

Aggarwala is hopeful that AI can address local governments’ operational challenges but said climate-related AI applications could fail to be useful to cities in the same way other urban technologies have been.

“We know that urban technology has fully conquered that age-old problem of ‘How can I get a burrito delivered?’ But it has not really addressed our housing crisis. It has not really fixed our transit systems,” Aggarwala said.

As AI tools proliferate, investments will be needed to teach the public sector how to use them, added Elijah Hutchinson, the executive director of the New York City Mayor's Office of Climate and Environmental Justice, in his remarks at the Urban Tech Summit. 

“It's encouraging to hear all of the different ways in which AI can be useful,” Hutchinson said. “We really need AI to also work for government as well and to be brought along in this transition.” Types of technology he would like to see include tools that assess how bus and bike lanes impact vehicle travel times as well as tools that help the city monitor noise and air quality impacts, “which are often very difficult to measure and can be fleeting.”

However, the climate opportunities of AI must be balanced with the environmental harms the technology poses, Hutchinson said. Computationally intense models are driving surging demand for data centers, which use large amounts of land, energy and water. Hutchinson noted that, on average, the water use of a data center for one day is equal to the water use of 3,000 New Yorkers. 

“There is so much more we don’t know in this landscape,” Hutchinson said. “Like any tool, what can help us can also harm us, and it needs to be used carefully.”

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By CivicPlus

Reading, Massachusetts, a town of over 25,000 residents, is known for its excellent schools, picturesque homes, and strong civic engagement. Situated just north of Boston, it has always prioritized community involvement. As technology evolved, Reading recognized the need to modernize its digital infrastructure, focusing on improving communication with its residents. Through partnerships with technology providers like CivicPlus®, the town transformed its approach to public services, creating a more responsive, user-friendly system that meets the expectations of its tech-savvy community.

Modernizing request management with data and a team-based approach

Before SeeClickFix 311 CRM was implemented, service requests were handled primarily via phone calls, which were inefficient and time-consuming. Jayne Wellman, Director of Operations, recalled, “There was no really good way of tracking resident service requests except people calling on the phone. People don’t want to talk to people anymore. That’s inconvenient.” In 2017, Reading adopted SeeClickFix 311 CRM, which allowed residents to report issues such as potholes and litter directly to the relevant departments.

SeeClickFix 311 CRM also helped with risk management. Wellman oversees road defect claims, while the Public Works department executes repairs. Cross-functional employees are given personal login access, so Wellman is not solely responsible for monitoring and assigning tasks. “We assess the issue and make sure repairs are made. We’ve only paid three pothole claims in the last seven years,” Wellman stated, emphasizing the system’s role in reducing risk and improving accountability.

The adaptability of Reading employees and SeeClickFix 311 CRM clear the air

In the summer of 2022, Reading faced a significant waste management crisis. When Republic Services acquired JRM Hauling and Recycling, their new automated trash collection system led to delays and missed pickups. Wellman explained, “People had reasonable expectations: they wanted their trash picked up as scheduled,” but delays became widespread, frustrating residents.

In response, the town turned to SeeClickFix 311 CRM to manage the complaints and track where trash pickups were missing. “We made a push on social media saying, ‘Post on SeeClickFix, let us know your address, your regular pick-up time,’” Wellman said. This allowed the town to pinpoint problem areas and take immediate action. To resolve the backlog, Reading’s Town Manager, Fidel Maltez, and the Public Works team conducted roadside cleanups and brought in dumpsters to manage the overflow. “We ran all of those complaints through SeeClickFix, using the mapping function to plan how to address neighborhoods,” Wellman explained.

The town held Republic Services accountable for the delays, making it clear that the issue was vendor-related. Wellman added, “We were able to demonstrate to residents that SeeClickFix was being used to track and address these issues.” The ability to manage service requests through a single platform helped the town keep residents informed and ensured that the vendor was held to higher standards of service.

Designing an award-winning municipal website

Along with SeeClickFix 311 CRM, the redesign of Reading’s website marked another step in the town’s digital transformation. The previous website was outdated, difficult to navigate, and lacked modern features. “The Town staff was working with an older website, and the functionality wasn’t up to date,” Wellman recalled. In collaboration with CivicPlus, Wellman and her team set out to build a website that would meet the community's high expectations for professionalism and functionality. “We wanted to minimize the number of clicks needed to find important information,” Wellman said. The site’s search function makes it easier for residents to access information quickly. The website also integrates social media links, allowing residents to engage with the town on various platforms. In January 2023, Reading’s website was awarded the Massachusetts Municipal Association’s Website of the Year for its size community. Wellman proudly noted, “It was gratifying to be recognized for our hard work.”

A model for digital civic engagement

Reading’s digital transformation has not only improved communication but also strengthened the town’s relationship with its residents. As Wellman concluded, “It’s a great town, and having these tools at our fingertips allows us to pivot to address any problem.” Through collaboration, innovation, and the strategic use of technology, Reading has set a new standard for digital civic engagement and service delivery. With continued investment in these tools, Reading is well-positioned to meet the evolving needs of its residents and remain a model of effective governance in the digital age.

“Every city is struggling to manage traffic,” said Doug Gilmour, TomTom’s global business development manager for traffic and travel products.

Last year, traffic on U.S. roads exceeded pre-pandemic levels and was the highest on record dating back to 1998, according to the Federal Highway Administration. Mapmaking company TomTom named New York City; Washington, D.C.; San Francisco; Boston and Chicago as the top five most congested cities in 2023. Drivers in these large cities each lost anywhere from 72 hours to over 100 hours per year in rush-hour traffic.

TomTom uses what is called “floating car data,” sourced from GPS-equipped devices such as onboard hardware in many vehicles or data from navigation apps on users’ smartphones. “With a critical mass of those GPS devices, we have a view to a significant proportion of the vehicle population,” Gilmour said. 

TomTom’s technology is included in a Frost & Sullivan white paper on how cities can use real-time traffic data from smart city companies to reduce traffic congestion and verify the outcomes of traffic management initiatives such as lowering speed limits.

In Wisconsin, the Department of Transportation uses TomTom data to monitor how much road work delays traffic. By eliminating the need for sensors and cameras, this data saves the state money, the white paper says. Amsterdam used the company’s data this year to see how a significant speed limit reduction affected traffic flow, helping the city engage with the community on questions about the change’s impact.

The white paper says it expects such data “to play an important role in enabling cities to plan and prepare to respond to a wider range of scenarios as a result of climate change, population growth, migration” and other factors. This data could, for example, help local officials understand the potential transportation network impacts of a large event that blocks traffic from certain sections of the city, the white paper said. That analysis might lead to actions like making more commuter trains available or ramping up park-and-ride opportunities.

Gilmour said cities can also use floating car data to determine “where to target infrastructure investments or policy changes” such as traffic-calming measures. “It makes for a more efficient road network and a more efficient city overall,” Gilmour said.

The National League of Cities and Google announced on Wednesday a report on how local governments can leverage artificial intelligence-driven technologies — and mitigate the risks they present. 

AI offers cities the opportunity to become more efficient, sustainable and livable, NLC CEO and Executive Director Clarence Anthony said in a foreword to the report. He pointed to applications such as optimizing traffic flow, reducing energy consumption and streamlining administrative tasks. 

However, not all cities are using or even have access to AI, which could turn “the digital divide that has plagued many cities into an ‘AI divide,’” Karan Bhatia, vice president and global head of government affairs and public policy at Google, said in a statement.

While the concept of AI has existed for decades, it burst into the public discourse in 2022 and 2023 with the release of generative AI applications that allowed people around the world to engage more directly with the technology for the first time, the NLC and Google report says. 

Generative AI, which can create new content like text and images based on patterns learned from existing data, is just one of numerous categories of AI. Other types of AI relevant to local government are predictive AI, which makes predictions about future events or trends, and perceptive AI, which interprets and understands sensory inputs.

Each of these types of AI brings distinct promise and pitfalls, says the report, which was spearheaded by the NLC’s AI Advisory Committee.

Generative AI, for example, can be used to translate public meetings and 311 calls or to develop chatbots that can respond to resident questions. However, generative AI can make mistakes. New York City’s chatbot made headlines earlier this year after providing residents with misinformation on topics such as housing rights and worker protections. 

AI tools may also reflect existing biases present in the data they are trained on; for example, they could reinforce existing inequitable resource allocation, the report says. AI tools also may pose data privacy and security risks and become a target for cyberattacks.

The report contains a toolkit that walks cities through the steps of getting started with AI, including conducting a landscape analysis, assessing readiness, developing use guidance and policy, and engaging the public.

Throughout the report, NLC and Google highlight how some cities are already using AI. Numerous communities have chatbots that help users find information about the city and its services, while Sunnyvale, California, gives residents who attend in-person city council meetings access to in-time closed captioning translation. Memphis, Tennessee, is using AI to find potholes by analyzing video footage from city vehicles and combining those results with existing data. Tucson, Arizona, meanwhile, is using AI software to predict which water pipes are most likely to fail next, helping the city prioritize maintenance and repairs.

But barriers to these applications remain: Resource constraints, concerns from city staff or elected officials and lack of political will to invest in technology are among the challenges cities face in implementing AI, the report says.

Google is piloting an online mapping tool in 14 U.S. communities to help city leaders understand how trees and highly reflective surfaces, like cool roofs, could help mitigate urban heat, according to a press release issued in September. 

“Cities can determine the neighborhoods with the highest heat exposure and vulnerability, and which cooling interventions could have the most reduction in surface temperatures,” said Mansi Kansal, Google Research product manager, in an email. The tool, which is not publicly available, Kansal said, applies artificial intelligence to satellite and aerial imagery to quantify potential reductions in surface temperatures.

Climate change-driven extreme heat presents a pressing challenge for cities around the world. Local and state governments are beginning to hire chief heat officers and devise heat action plans packed with short-term measures, such as opening cooling centers for the public to find respite on hot days, and long-term strategies, like increasing tree canopy.

Among the solutions that cities are turning to are “cool” pavement and roofs, which are designed to reflect rather than absorb sunlight. Some research has shown these reflective surfaces, deployed at neighborhood scale, can lower the ambient air temperature by several degrees Fahrenheit. However, some experts warn that this cooling effect is marginal compared with the public health benefits of increasing access to shade.

Google’s new tool marks another way city leaders can try to figure out the best heat mitigation measures for their community. It’s available in Austin, Texas; Baltimore; Boston; Boulder and Colorado Springs, Colorado; Los Angeles; Miami-Dade County, Florida; Nashville, Tennessee; New York City; Phoenix; San Antonio; Stockton, California; Tempe, Arizona; and Washington, D.C., Kansal said. 

The tool allows city planners to predict how changes in cool roof areas and tree canopy would change the average summer land surface temperature in their communities. It includes filters to show areas that see the highest temperatures and are most vulnerable, based on factors such as median household income and social vulnerability index, Kansal said.

Powering the tool is AI-driven object detection and models that account for local characteristics including how much green space a city has or how well the roofs on buildings reflect sunlight, the press release says.

The tool measures land surface temperatures rather than air temperature because the former provides higher spatial resolution and is available globally, Kansal said. Air temperature data is much more sparsely available and requires additional weather factors for accurate modeling. 

The land surface temperature data can give cities reliable insights that can enable decisions now on cooling interventions in vulnerable areas, Kansal said. Meanwhile, Google is working on longer-term research to model the effects of cooling interventions on air temperature. The tech company hopes to partner with more cities in the future to inform urban cooling strategies, the press release says.

The number of communities using automated speed safety cameras increased from 211 in 2023 to 222 as of March 2024, according to the Insurance Institute for Highway Safety. This growth comes as communities are allowed to use federal funds for such technology: The 2021 infrastructure law allowed states to spend up to 10% of their highway safety funds on non-infrastructure projects such as automated traffic enforcement. Previously, federal funds for speed cameras could only be used for school zones.

According to the National Association of City Transportation Officials, studies show that speed cameras reduce the percentage of speeding vehicles by 14% to 65% and can cut the number of serious injuries and fatal crashes by up to 44%. “Automated speed enforcement, if deployed equitably and applied appropriately to roads with the greatest risk of harm due to speeding, can provide significant safety benefits and save lives,” the U.S. Department of Transportation states in a 2022 report.

California last year authorized six cities to deploy automated speed safety cameras under a pilot program. New York City has over 2,000 speed enforcement cameras in school zones and experienced a 73% decrease in speeding at fixed camera locations from 2019 to 2021, resulting in one-third fewer pedestrian injuries, the city’s transportation department said. 

Meanwhile, the use of red light cameras has declined across the country. As of this month, 338 communities have deployed automated red light enforcement programs, a decrease from over 500 a decade ago, according to the Insurance Institute for Highway Safety.

However, some cities are increasing their use of this technology. Philadelphia, which implemented its red light camera program in 2005, had 34 locations installed as of fiscal year 2023, with others being added. In 2022, violations generated over $15 million for the Pennsylvania Department of Transportation, which distributed the revenue to 22 municipalities in the state for 28 traffic safety projects. New York City saw its average daily violations per red-light camera decline from more than 30 in 1994 to seven in 2021, according to a report by the city’s transportation department.

New York and other cities are also putting automated enforcement to work to protect bus and bike lanes. Camera-equipped transit buses in New York City began issuing $50 tickets to vehicles blocking bus lanes in 2019 and will start issuing tickets to those blocking bike lanes this year. Washington, D.C., began using cameras mounted on Washington Metropolitan Area Transit Authority buses in the city to issue tickets in 2023 to vehicles illegally parked, stopped or standing in a bus zone. Chicago is preparing to launch bus and bike lane enforcement in the city’s downtown in summer 2024 using cameras mounted on Chicago Transit Authority buses, city vehicles and fixed poles.

Drivers should expect more automated enforcement efforts, said Adam Snider, director of communications for the Governors Highway Safety Association. “There’s a number of examples of cities sort of deprioritizing traditional traffic enforcement and then, unfortunately, fatalities surging since then,” Snider said.

While these technologies have proven effective in reducing vehicle speeds and speed-related crashes, some communities may feel they are unfairly targeted or feel the cameras are just there to generate revenue. “More states are using [automated enforcement], but there are still some big public perception and policy obstacles to overcome,” Snider said.

ShotSpotter, a system U.S. police departments use to detect gunfire, resulted in New York Police Department officers spending hundreds of hours in a single month investigating incidents the officers could not confirm were in fact shots fired, according to an audit the New York City comptroller released in June.

But ShotSpotter contends the audit is focusing on the wrong metrics. 

The NYPD will have spent more than $54 million on the gunshot-detection service from the time the department started using it in 2014 until December, the end of its current contract with SoundThinking, the California company that owns the system.

The audit, led by New York City Comptroller Brad Lander, analyzed ShotSpotter’s accuracy over several months in 2022 and 2023. When the system was performing at its best, 20% of ShotSpotter’s alerts related to “confirmed shootings,” the audit found. But its performance was often below that level: Of the 940 alerts officers responded to in June 2023, for instance, only 13% corresponded to confirmed shootings.

That’s not the measure of accuracy the contract uses, however. The contractual standard the NYPD set was that ShotSpotter would detect and identify the location of 90% of outdoor gunfire incidents in the coverage areas, with some exceptions based on weapon caliber and suppression. (Suppressors, also known as silencers, muffle the sound of gunfire.) ShotSpotter reached its 90% target “in almost all boroughs except Manhattan, but when measured against the number of confirmed shootings, performance is far lower,” the audit states.

“It was surprising to me to learn how ShotSpotter wastes thousands of hours of NYPD officers’ time every year, and it doesn’t necessarily make New York safer for cops to, say, chase after a car backfiring,” Lander said in an interview.

In its four-page response, the NYPD said it “is limited in what it can consider a ‘confirmed shooting’ in conjunction with a ShotSpotter alert by the nature of police work and alerts which don’t result in the recovery of evidence (i.e. ballistics, property damage, shell casings/live ammunition, firearms, video, ear or eyewitnesses and/or victims).”

The audit criticizes NYPD for not collecting data the comptroller and the public could use to evaluate the tool’s effectiveness and economy. Without that evaluation, the audit “therefore does not currently support renewal of the contract,” it states. 

If NYPD renews the contract, Lander said, he would like to see a clause with consequences for the system providing too many false positives, including a structure to reduce the fee the city pays to SoundThinking if, say, more than half of all alerts sent to officers do not relate to a confirmed shooting.

How ShotSpotter works

In more than 160 cities, ShotSpotter has placed sensors in areas that are known to have high crime rates. The devices listen for sharp, loud sounds and transmit data to company employees who determine whether they sound like gunshots. If so, they notify the police. Due to how the sensors triangulate in a given area, the system can provide an exact location to police in about a minute.

What is often misunderstood is the human element at play here, says Tom Chittum, senior vice president of forensic services at ShotSpotter. “Our staff don’t just use their ears, but they have other elements to help them determine if a sound is a gunshot,” he notes. For example, they can listen for audio cues such as whistling associated with fireworks or look at the waveform of the audio data to determine whether that sound has a sharp rise and fall, or its distance from the nearest sensor.

In the NYPD audit report, the comptroller “is being disingenuous about what he found,” Chittum said. When NYPD records an unconfirmed shooting, “our system could have detected a real shooting, but the perpetrators may have fled, they may have collected casings, and witnesses don’t often stick around after calling 911.”

Chittum added that because finding evidence in low light can be challenging, when clients deploy “daytime follow-up” after a nighttime shooting, the recovery rate goes up.

Chittum and other SoundThinking executives have long said that ShotSpotter isn’t meant to replace law enforcement efforts or services such as 911; it’s only complementary. ShotSpotter can’t detect indoor shootings, for one, and the company doesn’t plan on updating the system to do so.

Other cities evaluating the technology

ShotSpotter has both advocates and critics. In February, Chicago Mayor Brandon Johnson said he is ending the city’s six-year contract with ShotSpotter, which had been one of his campaign pledges, saying that “Chicago spends $9 million a year on ShotSpotter despite clear evidence it is unreliable and overly susceptible to human error.”

In May, Houston announced it wants to end its four-year contract with ShotSpotter before it runs out in January 2027; Houston media reports found that only 5% of alerts from December 2020 through September 2022 led to an arrest.

After a one-year pilot program in 2023 in Durham, North Carolina, the City Council voted not to continue using the system. Philip Cook, professor emeritus of public policy and economics at Duke University, led an audit of ShotSpotter’s success rate in Durham. He shared three conclusions:

• For the 1,447 total gunshot notifications in the pilot area, 57% had only a ShotSpotter notification, 15% had both a 911 call and a ShotSpotter notification, and 28% had only a 911 call. 
• For the 282 confirmed gunshots, 26% had only a ShotSpotter notification, 34% had both a 911 call and a ShotSpotter notification, and 40% had only a 911 call. 
• The notifications only detected by ShotSpotter led to an additional 2.3 police deployments per day in the pilot area.

In an interview, Cook said that “The ShotSpotter system made it easier for officers to locate where the gunfire occurred, since when they get 911 calls, the caller could be blocks away and may not know exactly [where] the shooting occurred, and human error can also happen with those calls.” 

For the ShotSpotter notifications for which police did not confirm a gunshot, Cook suggested one possible reason: “The area where the sensors were installed [has] a high rate of drive-by shootings, so obviously it will be challenging for officers arriving five minutes later to find any perpetrators on the scene or to locate evidence.”

The Durham audit said researchers were unable to conclude if ShotSpotter’s technology led to a reduction in gun violence.

Beyond efficacy in crime prevention, other concerns about the technology’s use in Chicago have come from the Northwestern University School of Law’s MacArthur Justice Center and the ACLU. The two groups cite the Chicago inspector general’s report on ShotSpotter, which says the perceived aggregate frequency of ShotSpotter alerts in some regions encourages officers to engage in more stops and pat downs in those regions. 

Also, as the ACLU writes, “ShotSpotter’s methodology is used to provide evidence against defendants in criminal cases, but isn’t transparent and hasn’t been peer-reviewed or otherwise independently evaluated. That simply isn’t acceptable for data that is used in court.”

What does it take to quickly and efficiently clear the roads of winter precipitation in America’s snowiest major city? 

Syracuse, New York, which claims that title, uses dozens of snow removal vehicles, plows, and no fewer than three software systems, the city’s operations professionals say. The team has a big job: The city receives an average of 127 inches of snow, or nearly 11 feet, every year. 

Syracuse has been implementing Internet of Things and geographic information systems technologies for its snow removal since 2018, said Corey Driscoll Dunham, Syracuse’s chief operations officer. The overhaul of the system was prompted by a huge storm that January, she said.

“Between the mayor, the deputy mayor, our chief policy officer and myself, we spent the entire weekend driving around the city, getting messages through Facebook or text messages or phone calls or, you know, just chasing down complaints left and right about the roads,” Dunham said about the 2018 snowstorm, which lasted for 66 hours, according to news reports.

Dunham said it was clear the city needed a better way to respond to residents and provide some transparency about snow removal. Over the last few years, she; Conor Muldoon, the city’s deputy chief data and innovations officer; and the rest of the operations team have developed the interactive, real-time Syracuse Snow Operations Map. 

The city first tried building something in-house, Muldoon said, but by summer 2021, the team looked outward. The three-pronged software approach uses GIS company ESRI’s ArcGIS Velocity product paired with Samsara’s cloud-based location technology, which updates the Snow Operations Map with a plow’s location every few seconds. The third vendor is Rubicon, which offers a platform Syracuse uses year-round for management and routing of snow and waste removal vehicle fleets. 

“The Samsara is the underlying platform for knowing where the plows are, ESRI is a platform for ingesting all that information into a dashboard and communicating it out to the public, and then Rubicon is the platform for the drivers to dispatch communications,” Muldoon said. 

The real-time tracker allows residents to see which roads have been plowed and when. They can more easily see if the route to work or school is cleared, budget more time for travel, or decide to stay home. The Snow Operations Map also reports when there’s an impediment, like an illegally parked car, that is preventing a plow from going down a certain street. 

New York City adds bike lanes, salting progress to its plow tracking

Although New York City has had a map of snow plow progress, PlowNYC, for more than 10 years, the Department of Sanitation (DSNY) updated its operations software in 2023, ahead of predictions that the Northeast would receive higher-than-average levels of precipitation this winter. Its Bladerunner 2.0 platform, launched in December, helps the sanitation department streamline and centralize its prep and response to snow and ice and provides tracking data to help determine how and when to deploy staff. 

The Bladerunner software was first launched in 2015, a Department of Sanitation press release said. The city uses it year-round for waste collection and street cleaning operations. The recently released version 2.0 features better GPS tracking of snow removal fleet vehicles than its predecessor, Google Maps integration, real-time salting data, information about the status of protected bike lanes and a cloud-based system that handles more concurrent users with faster response times, the city said in a Dec. 14 press release. 

DSNY also is at its highest head count in two decades, the city said, and it has invested nearly $500 million in new sanitation trucks in the past two years, for a total of about 5,000 vehicles across all five boroughs. The city previously categorized streets in three tiers to prioritize snow clearing, but the investments and software have allowed it to eliminate that system, which had resulted in “different communities receiving different levels of service,” the city said in the press release. Now, every route and bike lane will be cleared when snow conditions warrant it, it said. 

New York City got its first meaningful snow in more than two years in January, and a second storm dropped about 3 inches of snow on Central Park Tuesday, but Belinda Mager, DSNY director of communications, said snowfall has still been limited compared with seasons past. 

“The system did give us more real-time information and situational awareness, allowing us to more effectively manage the storms we have experienced,” she said.

Startup gives Toronto snow plows traffic priority

Traffic optimization startup LYT, which uses cloud-based software to help manage the flow of vehicles in cities, recently expanded its services to snow plows in Toronto.

It seemed like a “no-brainer” that LYT’s platform, which works with existing technology on the roads, like traffic lights and cameras, could be applied to snow removal routes to make them more efficient and environmentally friendly, said founder and CEO Tim Menard. 

LYT’s platform already was using machine learning and artificial intelligence, along with real-time traffic data from smart sensors, to move emergency vehicles through traffic quickly. It’s now applying the same technology to Toronto’s snow plows: Sensors in the plows allow the city’s operations department to adjust the flow of green lights so that plows move more quickly through intersections and neighborhoods. 

Prioritizing snow plows in the flow of traffic offers financial and environmental benefits to cities, Menard said. Less stopping at intersections reduces wear and tear on snow removal vehicles, and it helps the plows clear main roads faster. In addition, snow removal vehicles are often also spreading salt on roads as they travel, so more continuous movement allows for more equal distribution of salt. Salt build-up is a large contributor to potholes, Menard said.

Less stopping also means vehicles use less fuel and produce fewer emissions. Two of the cities LYT works with report they have saved a combined $600,000 in fuel last year and reduced carbon dioxide emissions levels by 1,000 metric tons, the CEO said.

The value of transparency

Three years into the Snow Operations Map project, Syracuse officials said its use by residents continues to grow, showing that the demand for information transparency remains strong. 

The city prioritizes clearing snow from the main roads and roads that provide access to hospitals, but the real-time information shows residents that it aims to be equitable in its snow removal, not favoring certain neighborhoods or areas over others, Dunham said. 

“These decisions are being made by data, which will, hopefully … either restore or maintain the trust that residents have in local government,” Dunham said. “These decisions are being made with the limited resources that we have, and [the service is] going to the greatest areas of need.” 

The city of Stockton, California, plans to use vehicle-mounted cameras and artificial intelligence software to help its understaffed police department detect and report code violations like overgrown lawns, improper parking, peeling paint, boarded windows and graffiti.

Stockton’s city council unanimously voted in June 2024 to enter into a $237,600-per-year contract with City Detect, after running a five-day pilot program using the company’s technology in early 2024. The contract will run for a year with optional second and third years.

The city hopes the technology will allow code enforcement officers to spend more time proactively finding violations and educating the community rather than primarily reacting to complaints, according to the legislation text.

Booming interest in AI has left cities grappling with how to use it to make local government more efficient while minimizing negative unintended consequences. 

“AI is going to work its way into your city at some point,” whether it’s through a vendor or an intern, said Stephen Caines, chief innovation officer for the city of San Jose, California, at Smart City Expo USA. He advised cities to figure out the rules of the road now. 

Stockton will be the first California city to use City Detect’s software, officials told CBS News. The company uses vehicle-mounted cameras to analyze scenarios throughout the city, with its machine learning system analyzing the built environment “exponentially faster than traditional reporting methods,” according to the city’s legislation text. 

Locations are given a relative blight score, which reflects their blight or deterioration compared with other areas, the document says. That score allows code enforcement officers to prioritize resources and interventions.

The city says its five-day pilot with the technology in January identified 4,000 code violations at over 2,000 locations. 

Some other cities are using AI technology similarly. Memphis, Tennessee, for example, is using vehicle-mounted cameras to spot potholes. Columbia, South Carolina, is also testing City Detect’s technology with cameras mounted on garbage trucks. However, some residents have expressed privacy concerns, local newspaper The State reports.