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7 Ways Smart Cities Use Location Intelligence for Public Asset Management

Authors Photo Precisely Editor | October 26, 2020

A wave of new innovations is enabling government leaders to implement “smart city” technology to improve services to their citizens, increase energy efficiency, and save money. Municipalities are using Internet of Things (IoT) sensors and improved network connectivity to gather data on traffic, energy, air quality, mobility, public infrastructure assets, and more.

All of that data is being enhanced and optimized with powerful location intelligence and asset management tools. The net result is cost savings, energy efficiency, and improved services.

Parking, Public Transportation, and Streetlights

It can be difficult to find a parking space in Barcelona, Spain. Thanks to a network of smart sensors, however, information about available parking spaces is made available in real-time to drivers throughout the city. By directing residents to an open parking spot, the city is reducing traffic and pollution while saving its residents time.

Users of public transportation benefit as well from smart city technology. Sensors aboard city buses, for example, can detect whether a bus is ahead of schedule, behind schedule, or right on time. Armed with this information, many cities are providing notifications to users of public transportation, informing them of predicted arrival and departure times.

Some cities are even taking this a step further. If a bus is slightly ahead of schedule, for example, the timing of traffic lights can be adjusted slightly so that the bus is not compelled to sit idle at the next bus stop.

In London and Quebec, energy-efficient smart streetlights are serving multiple purposes. Sensors detect the presence of pedestrians or vehicles, and the lights are dimmed or turned off when not needed. This feature alone can save as much as 30% on energy costs.

Smart streetlights are helping in other ways as well, though. They function as Wi-Fi hotspots and feature charging outlets for mobile phones and even electric vehicles. Surveillance cameras installed alongside the streetlights safeguard the community against crime. Some even have air quality sensors, providing valuable environmental data for city officials.

Smart Waste Management

While the examples cited above are easy to understand and resonate with a broad audience, there are plenty of other use cases that are perhaps a bit less sexy, but which nevertheless have very real benefits for urban communities.

Many of us take for granted that when we toss a used coffee cup into a city trash receptacle along the sidewalk, someone will eventually turn up to collect that trash and haul it away. Historically, that kind of service has been provided based on routinely scheduled operations. In other words, we can make a pretty good guess, based on past history, as to when that trash can and will need to be emptied.

Logistically, there are several inefficiencies here. For one thing, a trashcan along the main thoroughfare might fill up much faster than one that is stationed only a block away. This means that a collection truck may end up spending a good deal of its time servicing receptacles that are less than half-full.

The core problem, though, is that without smart technology, we really don’t know when any of the trash cans need to be emptied. If we add sensor technology and connectivity, we can have a real-time view of the city’s waste management needs. We can allocate resources where they are needed and when they are needed, rather than making a best guess about the situation. That saves time and money. With fewer trash collection vehicles on the road, it also reduces traffic congestion.Row of bicycles ready for renting, Location Intelligence

Bike-stands, Trees, and Parking Meters

When we start to drill down into all of the various assets that are managed and serviced by municipal government, public asset management begins to look like a daunting task. Technology can rein in that complexity.

Many of the larger cities throughout the world have implemented bicycle sharing programs centered around public bike-docking kiosks. When someone rents or borrows a bicycle, those kiosks are able to detect how many bikes are available and share that information to mobile phone users throughout the city. Sensors installed on each bicycle can communicate maintenance requirements to city officials so that units can be efficiently and promptly repaired and put back in service.

The same principles can be applied to virtually any public asset. Parking meters, for example, will stop producing revenue when they are out of service. By establishing two-way communication between devices such as parking meters and a central asset management system, city officials can be notified promptly of a needed repair and can use mobile technology to deploy maintenance resources in the area to fix the problem.

Trees also require regular maintenance. While it may not make sense to install IoT sensors in the city’s trees, the fundamental need for systems to manage scheduled maintenance remains. By enabling the smart allocation of resources around maintenance tasks of any kind, local governments increase efficiency and save money.

Compounding Benefits with Location Intelligence

All of these connected technologies result in a high volume of information that was never available before. Consider what happens when we begin to combine that with some of the other location-based data available to city managers.

If we return to our bicycle sharing example, we might discover some interesting new possibilities. Let’s assume, for instance, that routine use of the bike-sharing service for one-way trips results in a surplus of bicycles in the waterfront area of the city. As a result, city workers have to routinely pick up bikes from the waterfront, load them into a truck, and return them to kiosks in the downtown area. That’s a lot of work, and it costs money.

What if city managers were to analyze mobility data to understand where people are at various times of the day? What if they used that data to establish a schedule of incentive pricing for one-way bike trips back to downtown? To take this example a step further, program managers could use mobility services to promote the new incentive pricing to pedestrians who frequent the waterfront area.

The net result will be a win-win; more residents will benefit from using a community resource, and the city will save money in the process. When you consider the volume of data available through smart city technologies and combine that with external location data, a wealth of new opportunities emerges. Location intelligence makes it all possible.

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