Thirty years ago, when the world was first exposed to the internet, we experienced some radical changes in our lives. Everything started getting digitized, and technology took the front seat in every economy. From thereon, the importance and relevance of the internet have only been growing. Initially, the purpose of internet media was to offer convenience and provide an alternate way to store crucial data. It led to articulated data management that changed how giant corporations functioned.
Until the last decade, we only saw addendums to the existing internet technology, but that is set to change now. We are now ushering into the era of another revolutionary technology derived from the internet, artificial intelligence. Initially, AI and machine learning applications were seen as quite limited, and only tech companies could properly implement AI in their routine operations. However, with the evolution of neural networks and deep learning algorithms, literally, every industry has found a place for AI in its systems. It has led to some positive development in crowd management operations too. For more information on security services check out NHN Group.
This article will discuss the implementation of artificial intelligence in crowd management.
AI and Crowd Control
Crowd management is not a one-way lane. There are several aspects attached to this complex job. Crowd management does not mean that the authorities are supposed to control the foot traffic alone, and they have to consider the traffic patterns, chances of a stampede, public protocols, etc. This task requires the highest level of human diligence to avoid getting into trouble with the public.
Therefore, complete automation of the crowd management process is not currently possible. However, AI can help us automate some tedious tasks, which could have led to human errors. Machine learning algorithm developers use various images to teach the system about crowd movement patterns.
The images usually contain various information, such as unique angles, discernible patterns, and non-stationary or non-living objects. The task of deep learning algorithms is to distinguish every detail from each other. Therefore, millions of images are used so the algorithm can adapt to every new information. Then, the extracted information is stored as crucial data in the system. This stored data is run through a series of yes/no decisions to reach a final output.
The public service department can use AI-powered software for headcount, identify problematic movement patterns that could lead to chaos, and check crowds’ compliance with government regulations. In the present reality of a worldwide pandemic, the relevance of crowd management software increased because it could now be used to track infected objects and high foot traffic areas. You can learn more about how crowd management can be tracked and automated by pursuing Great Learning’s artificial intelligence courses online.
Use of AI Crowd Management by Finland
The Nordic countries have constantly been at the forefront of the digital revolution, which might be due to the sense that they have a relatively small population size and relatively large resource allocation. Hence, crowd management per square kilometre is pretty straightforward.
Therefore, these countries have the liberty to test new systems that could assist humans in day-to-day operations and bring better efficiency. On similar lines, Finland has been one of the few countries experimenting with AI-powered crowd management.
In August 2020, Finland deployed AI software and attached them with the already existing public monitoring cameras. The purpose was to figure out the volume of the crowd at any given place and time and accordingly plan the deployment of security personnel. Additionally, the AI software used in Finland is trained to mimic human diligence, so it is well-equipped to alert the appropriate authorities as soon as the crowd in a particular breach the safety protocols.
Also, Finland realized that applications of crowd management software are much more than anticipated. Hence, they now use the same software for population mapping and resource allocation. Authorities use the assistance of crowd management software to figure out the migration and resource allocation. The software could help map the demographic changes in rural and urban areas. Additionally, the government could plan its regulations and policies.
India implementing AI crowd management
Indian religious carnivals are known for their magnificence and belligerent traffic. Several thousand people attend these “Melas” every year and take a dip in the holy river of the Ganges. Usually, such carnivals are a couple of weeks long, which calls for diligent planning in advance. Authorities stay on their feet at least one year in advance to monitor the crowd influx and monitor public movement.
The allocated sites for these carnivals are usually smaller, leading to high population density. It is one of the leading causes of minor stampedes in “Melas.” Hence, some assistance is required to minimize human error in decision-making. For this reason, the security cameras used in these locations are now powered by data-driven AI software. The purpose of the software is to monitor the crowd movement and track any suspicious activities. Therefore, when a problematic movement triggers the algorithm, an alert is issued to the authorities so they can take action well in advance.
In the 2019 “Kumbh Mela” organized in Prayagraj, the Uttar Pradesh (a state in India) government used crowd management AI software, which yielded promising results. The “Mela” turned out to be a huge success and was applauded for its efficient administration. Several other Indian states have now drawn inspiration from AI-enabled security cameras and have committed to implementing them in their carnivals.
Conclusion
The applications of AI and machine learning are increasing every day, and several departments are starting to realize the endless potential that the future of AI holds. Industries today seek software that could assist their human workforce in better decision-making. This is an excellent time for developing deep learning algorithms because of the bulk of data that forms a robust neural network.
Additionally, the development of image recognition technology is critical in implementing AI-powered tools. If you are keen to build a career as an AI and machine learning specialist, sign in to Great Learning. Here, you will find plenty of courses. Choose a relevant AI and ML course from Great Learning taught by industry experts, that will help you build a good profile.
