Edge AI Enhances Smart Cities
See how edge AI is adding intelligence to dumb devices and bringing smart cities into the future
Urban areas are growing quickly. Consequently, governments are searching for ways to deliver their services more effectively. Edge Artificial Intelligence is a rapidly emerging technology platform with tremendous potential. Available in applications ranging from smart meters to smart lighting, it streamlines processes, improves efficiency, and lowers costs.
Similarly, world demographics are also evolving. By 2050, 68% of the world’s population will live in urban areas, more than double from 30% in 1950, according to the United Nations. The growth is straining city infrastructure at a time when budget increases are small or non-existent. Technology has the potential to create smart cities, which leverage new solutions and dramatically improve service delivery.
Edge and AI Add Intelligence to Dumb Devices
The applications are boundless and include areas like traffic management, smart meters, parking space management, energy grid improvement, intelligent streetlights, renewable energy, and emergency services. A couple of key building blocks are needed to create the change.
Edge computing moves analysis and decision making closer to where the data is generated. Therefore, information does not travel back and forth to a far-off data center. The lower latency enables systems to work faster and more effectively; reducing the risk of service delays and outages which lowers expenses.
IoT is Not so Smart
For the last decade municipalities have been deploying Internet of Things (IoT) sensors of all types in all sorts of applications from measuring foot traffic on street corners to detecting when a trash can needs emptying. IoT turned traditionally dumb devices like parking meters, video cameras, and energy meters, into intelligent solutions.
But this generation of devices, which we naively called Smart not knowing what we know now, was so far from the truth. A more accurate term we could have settled on was “connected” home, city, or grid.
The “smart” part is only just beginning to happen now.
The problem is many IoT devices are not smart enough to act upon the data themselves. So whatever data they collect, they have to stream it to the cloud, regardless of its value, or lack thereof.
This left city agencies with more information than they know what to do with, and a whole new type of headache – a hefty cloud services bill to ingest, process and store all of that data; 95% of which in most cases turns out to be non-actionable, and did not have to make the trip from the edge to the data center and back again.
Edge AI to the Rescue
Coupling edge computing with AI on small devices addresses that problem. However, AI applications operate differently than legacy software. Running AI solutions efficiently requires special purpose chips, so this is not something we can retrofit to old devices. Vendors will need to build totally new devices for Edge AI to enable new capabilities beyond IoT.
These products will be able to correlate data points, draw deductions and act upon them, on their own without relying on the cloud or overloading it with data.
Edge AI Moves Municipalities Beyond IoT
Edge AI applications running on newer, smaller, more efficient hardware are becoming the foundation for next generation smart city solutions – going far beyond what was accomplished with IoT. Whether it’s AI enabled cameras on every street corner or sensors on conveyor belts in municipal airports, these new systems deliver a higher level of functionality, with far more efficient use of the cloud and network resources, than preceding IoT solutions. Here are a few of the benefits:
Benefits of Edge AI for Smart Cities
Lower Network Latency
Move computational power closer to the data source and minimize data transmission latency since information does not travel to and from remote, centralized servers.
Better Reliability
Reducing the reliance on a central system makes Edge AI city systems more reliable, minimizes downtime, and boosts system availability. Unlike IoT, in some cases, applications continue to run even when equipment is disrupted, or when failures occur.
Bandwidth Optimization
Alleviate the burden on the network infrastructure by processing and filtering data locally. Only relevant information is transmitted over municipal networks, reducing bandwidth requirements and lowering data transfer costs.
Deliver Real Time Data
Special purpose embedded systems generate, collect, consolidate, analyze, and present information in real-time, which improves decision making and speeds up service delivery.
Enhance Privacy and Security
Process and analyze sensitive data locally. Without the requirement to transmit it to remote servers, the potential exposure of confidential information to external threats and the number of potential breaches is minimized.
Lower Provisioning Costs
Replace cumbersome legacy systems, which require a great deal of manual input, with modern frictionless solutions that are simpler to deploy.
Cut Technical Debt
Spend less time servicing older devices that are prone to problems with new solutions that feature sophisticated self-diagnostic and self-healing capabilities.
IoT and Edge AI’s Many Smart City Applications
The new computing framework’s potential impact is enormous. Global smart city technology investments are on track to hit roughly $6 trillion in 2030. Emerging technology could change just about all local government operations.
Building Security
Agencies implement smart access controls, including biometric systems like facial and gait recognition, to secure access to buildings. Intelligent street and parking lot lighting provides more visibility in remote areas and at night, so streets and neighborhoods become better lit and citizens feel safer
Smart Grid
Sensors and smart meters analyze energy usage and demand in real time. With edge AI, public utilities better balance supply and demand because they understand what is happening in real time.
They detect faults or outages as they occur and respond to them faster and more efficiently. Smart building ventilation systems constantly readjust themselves in order to maintain optimum temperature and air quality.
Analytics enable the government to better track natural resources, like water and energy. Steps can be put in place to reduce unnecessary usage, such as a slow leak, and maximize their potential benefits.
Traffic Management
Real-time data from traffic sensors, cameras, and Global Positioning System (GPS) is consolidated and provides a fuller picture of roadway usage. AI edge applications detect congestion, shift loads to underutilized routes, and manage traffic signals in real time more efficiently to optimize traffic flow, as well.
The solutions reduce traffic congestion; minimize travel time and use of fossil fuels; lower transportation infrastructure wear and tear; and reduce vehicle and pedestrian accidents.
Emergency services become more efficient. AI Vision technologies scan traffic flows through a busy downtown, notice when an accident occurs, zoom in on the incident, and immediately notify the emergency personnel, medical, police, and fire department.
After examining a live stream, they evaluate the damage and danger bring along any special equipment that may be required.
Infrastructure Management
Sensors are embedded in infrastructure, like bridges, roads, and power plants, and monitor each structure’s health. The data helps staff understand maintenance needs, predict failures, prioritize infrastructure investments, and enhance the items’ long-term sustainability. For instance, road repairs become proactive rather than reactive: video systems note potholes on city streets and send notifications to work crews.
Environment Monitoring
Data from air quality sensors, weather stations, and pollution monitors is collected. Cities rely on AI analytics to understand current conditions, detect pollution levels, and implement measures to improve air quality. Better measuring the impact of government programs reduces carbon footprint and improves citizens’ quality of life.
Public Safety and Security
Provide real time analysis of surveillance footage, so cities detect anomalies, identify potential security threats, and respond to problems faster and more efficiently. Applications include facial recognition, license plate matching, and gunshot detection.
Public Transit Systems
Provide real-time tracking of buses and trains. These systems support dynamic scheduling and mobile apps so public transportation operates more efficiently and the customer experience improves.
Waste Management
Sanitation departments monitor bin fill levels and optimize waste collection routes. They implement predictive maintenance for waste management equipment. These changes reduce costs, minimize environmental impact, improve efficiency, streamline waste collection, and enhance recycling efforts.
Public Healthcare
Support remote patient monitoring, real-time health data analysis, and medical device management. By processing data locally at the edge, healthcare providers ensure timely interventions, improve patient outcomes, and secure confidential information more easily.
Smart Cities Need Smart Partners
In essence, edge AI computing serves as a critical enabler for more efficient operation. Cities can use these solutions to support their growing populations more effectively. They extend the breadth and depth of their services and deliver them in a more cost-effective and more productive manner.
However, they face a challenge getting started: edge AI smart city apps are largely non-existent and have to be built from scratch, a complex process. The work requires specialized expertise in embedded systems and porting AI models to different hardware.
The right partner can help government agencies evaluate different ideas and quickly develop a proof of concept to assess the viability of the solution. The right partner is an embedded systems company that works with silicon suppliers, network equipment vendors, software companies, and AI experts to create Edge AI applications.
embedUR is one such company. We have been designing custom embedded systems for decades and have many satisfied clients around the globe. We work closely with chip vendors and can help your agency leverage Edge AI to improve operations and service delivery.
Got game-changing ideas? Contact us, we’ll help you understand if they could fly. And if so, we can help you fit all of the pieces together, so you reap Edge AI’s tremendous potential. Read more on how the Edge Computing Revolution can help accelerate your products to market.
