Deep Learning Technologies in Smart Cities
In this era, technology is evolving faster than anything. Artificial Intelligence (AI) is impacting the future of virtually every industry and acts as one of the major pillars of technology. It is driven by the advancements in the areas of Big Data, Machine Learning (ML), and Deep Learning (DL). Data serves as the cement holding this pillar strong. DL is the central technology behind a lot of high-end innovations like driver less cars, voice control in devices like tablets, smartphones, hands-free speakers, and many more.
One of the industries significantly impacted by AI/DL/ML is the smart city infrastructure. Solutions for smart city infrastructure provide utilities, transportation, and city services to the citizens. Smart city solutions use technology-based elements like IoT sensors, applications, networks, cameras, etc. to gather information related to traffic congestion and provides satellite views using GPS-enabled tracking systems. This load of information in turn is translated to notify users about the air quality, pollution levels, and real-time traffic views.
Improving the lives of the citizens
The Traffic Management System (TMS) provides real-time updates to the users, like notifying up-to-date status on the road congestion or accidents to the commuters ensuring their safety. There is an urgent need to make this information available to the maximum number of users in a viable manner.
Smart cities are designed to make life convenient and comfortable for its citizens. A significant amount of city data is generated from Information and Communications Technology (ICT) enabled on various devices. Data Analytics (DA) is central to processing this deluge of data where AI delivers meaningful and tangible views of reality. AI can understand the functioning of cities and their changes where IoT is used to interconnect seamlessly, control, and provide insights.
Both AI and IoT go hand-in-glove to implement smart solutions for a smoother traffic flow in the city. A case in point is when connected traffic lights receive data from multiple sensors and when processed using AI/IoT provides real-time traffic information to the users, thereby reducing road congestion.
Smart Cities and the emergence of advanced technology
DL requires large amounts of data and can detect patterns and features collecting insights through IoT networks. An essential component of smart cities is “smart monitoring”, which is characterized by a solid invisible bridge between the wire/wireless sensors and the information infrastructure which consumes the data and provides intelligent analytics to the users.
Smart City systems aim to support municipal systems, local authorities, and the government in various use cases, including reduced crime, cleaner air, more orderly traffic flow, and more efficient services for the citizens.
Benefits of using Deep Learning Technologies in Smart City Solutions
Smart city solutions provide users with a vast range of services, including intelligent transportation, smart healthcare, smart parking, and smart utilities, etc. DL technologies help build better smart traffic solutions by transforming traditional elements of the city and the way it operates in terms of connectivity, transportation, security, and safety.
- Helping local officials in better decision making
- Providing security and surveillance solutions
- Improving the standard of living of the citizens
- Ensuring human life safety through road surveillance
- Capturing real-time information for road-users
- Improving traffic and connectivity
- Providing accurate early warnings to residents
Thus, DL Technologies can help local authorities and the government achieve better decision-making through smart governance and 24*7 city surveillance.
At EFKON India, a global leader in the Intelligent Transportation System (ITS), we help clients by providing innovative products and solutions in emerging AI technologies. By offering products built within the ecosystem of AI/DL/ML, EFKON is at the forefront of providing solutions to our clients in services for smart city infrastructure development. Employing state-of-the-art Graphical Processing Units (GPUs) for processing live feeds from strategically positioned cameras within the city, we provide software products that perform real-time analytics for incident detection on city roads and highways, using hardware and the software stack based on NVIDIA’s GPU cards and open-source frameworks like Metropolis.