Artificial vision to achieve more efficient cities
The possibilities to apply artificial vision in different situations of our everyday life make this technology the best ally to promote more efficient and sustainable cities.
According to estimates by Allied Market Research , the global artificial vision market will grow by 16% per year in the coming years to reach 41 000 million euros in 2030. This is not surprising if we take into account that artificial vision or computer vision technologies with artificial intelligence already resolve issues in an infinity of companies’ sectors and activities (health, security, field operations, circular economy, shops…) and more and more this technology will be used to launch new applications and uses to promote more sustainable activities within more efficient cities.
For example, for the intelligent cataloging of urban furniture in a city. Having urban furniture checked and identified takes a lot of time and effort. Through the incorporation of cameras in public transport vehicles like buses, our AI algorithms, next to artificial vision, would not only be able to make inventories, but would also be able to detect the state of conservation of bus shelters, banks, street lamps, solving vandalism problems almost in real time.
These same cameras located in public transport or autonomous vehicles could help in the detection of graffiti or architectural barriers. According to INE, in 2020 a total of 4,38 million people’s residents in Spanish households had a disability or limitation, mobility problems are the most “common” disabilities. The use of artificial vision would permit the detection of architectural barriers and possible points of conflict: traffic lights, tactil signalisations inadequate or defective, visual or audible when crossing; Elements that make difficult the passage of strollers and wheelchairs; Uncivil behavior with cars, motos, or bikes parked in a transit area…
This is also a valid solution for the management of the traffic. Since it’s responsible in part for pollution in cities, the regulation and optimisation of the traffic in an autonomous and intelligent way, would allow us to adjust the interval between the traffic lights in function of the density occupation of the streets and not by a recurring cycle of time, contributing to reducing travel times and pollution in cities.
Artificial vision is also vital for the development of autonomous vehicles because it will be able to read and interpret road signs, take decisions to let the way to emergency vehicles or to identify in a reliable way others cars on the road or pedestrians on the sideway. We also use artificial vision to control and count vehicles that come in and out of a garage, to prevent robberies or to know the occupancy rate of a parking area. But the same as used for vehicles, we can also use it to count endangered animals by placing cameras in determined spaces or analyzing drone footage.
In the security field, artificial vision is frequently used in scanning devices for the identification of people (or temperature, like during the pandemic) and objects or for access controls. Unlike other methods like sensors, artificial vision can even anticipate human behaviour by detecting the suspect behaviors. For example, to prevent the robbery of materials or like that already happened, to prevent the robbery of gasoil of your truck fleet.
The visual scan of people can also identify any dangerous objects, like firearms or blades, thinking about access control in public buildings (town halls, airports, stations…) or performance venues.
In the same line of prevention and access control, we bring an artificial vision into the field of labor risk prevention. According to the latest data from the ministry of labor, the weekly mortality in work accidents increased by 10% last year, with almost thirteen deaths every seven days. With the computer vision technology and thanks to the development of algorithms based on neural networks (AI), the possibility to improve the security measures against the risks at work is infinite. For example, to scan in real time in a multitude of environments and situations, the correct use of equipment like: masks, security helmets, safety glasses, work gloves, reflective clothes, toolbelts, among other things. Thereby, it’s the system itself that, after analysis and identification, decides automatically if it allows or not to the worker to have access to his work.
The good thing about artificial vision is that its possibilities of application and its advantages are unlimited. So we can simply wait for an opportunity or, like we do in Seitech, work to create this opportunity and to meet a need.
