Imagine there is a city struggling with waste management, traffic problems, safety of citizens and a few other issues that demand immediate yet ‘deep’ attention. Traditional methods have been employed but the results are not satisfactory. The city needs to be “smart” in its approach. So, how does it become smart?
Well, a possible answer is by “deep learning”.
The city needs to re-invent its approach, learn what’s wrong at a deeper level and totally change the way things have been getting approached. Smart cities aim at improving the quality and performance of urban services by employing digital technologies. Data analytics plays a key role in helping cities become smart.
When we have data and facts at hand, we can extract a lot of information out of it and visualize what can be done. For instance, installing sensors in a city to collect a huge volume of data in the form of surveillance videos, traffic data or anything else can help. How? Well, the data collected can be fed to machine learning algorithms to get results and observations which otherwise would have been missed anyway.
Let’s dig deeper into this and try to understand how to “deeply learn” things with the help of a few use cases.
Solid Waste Management/Vandalism
Talking about the whole of the Earth, studies indicate that the annual solid waste will hit the 2.2 billion tonnes mark by 2025, which is huge!
With solid waste hitting this huge mark, no wonder it would cost equally huge (somewhat around $375.5 billion) to manage this waste.
Clearly, the traditional methods are not going to help.
Employing deep learning algorithms can be a possible way out.
Mirasys is a professional provider of deep learning-based video analytics solutions that can be used for the implementation of “Swachh Bharat Abhiyan”. The software can assist with the monitoring of timely cleaning of bins, detection of garbage, and keeping a check on sanitization workers. The concept helps eliminate the need for manual, slow methods and increases the efficiency manifold.
Traffic Management
With population density escalating at an alarming rate and roads getting congested day by day, there is a pressing need to perfect the traffic management system. It does seem challenging to come up with something that helps prevent accidents, or classifies vehicles but is also cost-effective at the same time. A possible approach to improve the state of traffic in packed areas is to call deep learning algorithms to rescue. Deep learning-based analytics methods devised by Mirasys use live or recorded videos from all over the city, captured by cameras, to help detect cases of parking violation, abandoned bags, accidents, helmet defaulters, triple riding, speeding, parking in no-parking zones, wrong-way driving, and traffic congestion.
The system works based on Neural Network Models and Deep Learning of object detection coupled with computer vision technology and a few other methods and algorithms. The system is in action in Panchkula city already!
Citizens’ Safety
The world is generating data at a surprising rate. However, there isn’t any fun until we know how to harness “information” from this “data”. Machine learning coupled with artificial intelligence can be (and has been!) helping police departments all over the world make wise and informed decisions based on facts and data. Intelligent video analytics methods can be used to enhance the safety of the citizens as well. Be it detecting and recognizing the pattern of demonstration and conflicts in a group of people or detection of loitering or people climbing barricades, intelligent video analytics can be of great advantage. Capital cities like Bhopal, Gandhinagar have been actively depending on deep learning methods and video management software for providing an enriching experience to the citizens and tourists.
Advanced 3D Calibration
Three dimensional data is one of the most valuable sources of information in the digital world. It helps analyse the entire geometry of the sensed objects and scenes. The availability of huge three dimensional datasets and computational power has made it possible to apply deep learning algorithms to learn relevant tasks on three dimensional data such as segmentation, recognition and correspondence.
Activities of the likes of dwell detection, enter and exit detection, directional detection, counting of objects followed by their classification, and even camera tampering are not impossible anymore. Modern deep-learning based video analytics technology solutions have totally revolutionized the way we are getting things done. The smart city project for the holy city of Varanasi is an example of Mirasys in action. Focusing on the city’s socio-economic growth, cleanliness, and smooth traffic movement, Mirasys’s deep learning-based analytics were customised as per the requirements. The unsupervised learning methods by Mirasys including comparative, adaptive and hermeneutic methodology for various adverse conditions assisted in solving challenges such as tightening city security, detection of congestion, camera vandalism, parking violation and object classification. Using GPU and Deep Learning to segment live or archived videos into structured data with rich metadata, that can actually be used to derive conclusions is indispensable to achieving highly actionable insights, be it for business intelligence or data-driven safety, security, and operational decision making.
We hope to witness a lot of other interesting applications of deep learning based video analytics in the coming few years.
