Wintry and snowy conditions of weather have a certain effect on traffic and transport. Now, this can be realized in different ways. For example, visibility on highways rapidly diminishes when it's snowing, and it is harder for drivers to maintain an even speed. Similarly, in the transport realm - train tracks are known to contract when it is cold, as a consequence of the temperature's effect on the metal.
In this article, we take a look at how video analytics can simplify traffic and transport processes, and the areas in which it can be implemented in a viable way.
Why is Video Analytics important in Snowy Weather?
Now that we have laid out the basic premise for your understanding, it is time to explore the context behind it.
Snow is, simply speaking, an inconvenience. It affects the mobility of vehicles and pedestrians, negatively impacts visibility, causes roads and sidewalks to go icy and thereby, potentially dangerous to drive on.
There is a fix for most of these - drivers can affix snow tires for when the winter months arrive, and municipal governments work hard to clear roads of snow on a timely basis. However, the risk of an accident or injury still remains. This is where video analytics platforms such as Isarsoft Perception come in.
With video data being processed and analyzed consistently, users can perform a range of functions. Some examples would include heat maps to assess factors such as speed, dwell time, path, and position for moving traffic, georeferencing, pedestrian safety, and train detection.
Benefits of Georeferencing
Location and Speed Detection
Georeferencing allows users to track the location of objects within the specified area, and also determine derived speed in meters per second. This can be later applied to a variety of scenarios - regulation of traffic, prevention of overcrowding, securing safety protocol by setting a speed limit and governing moving vehicles by the same, measurement and analysis of crowds and general optimisation.
Measurement of People/Traffic Density
Georeferencing enables the user to assess and determine object density. Since Isarsoft Perception’s georeferencing features are trained to detect both pedestrians and vehicles, it can therefore be used to measure object density regardless of circumstance, i.e, a traffic-laden highway, a crowded sidewalk, etc.
Flexibility and Ease of Use
Isarsoft Perception’s georeferencing feature allows room for error. As already mentioned, fine-tuning of the coordinates is entirely possible, owing to clearly defined boxes for latitudinal and longitudinal coordinates.
The coloured points provided for area definition are easy to use, and can be adjusted according to requirement.
The data display is live, and comes with an accompaniment of a graph that is updated in real time depending on fluctuations.
Read more about how Isarsoft Perception implements georeferencing here.
Applications of Video Analytics in Snowy Weather
It makes sense that traffic management becomes harder in the snow. Video analytics makes the job much simpler, and can be applied for specific use-cases.
To start with, video analytics can be used to detect and identify vehicles, pedestrians, or road conditions that require attention - in spite of the reduced visibility due to snow. This significantly impacts operational efficacy as well as time of commute in the winter months. The detect feature is also heavily used when on the lookout for anomalies, whether deliberate or accidental. This includes anything from errant driving to wrong turns and other violations of traffic rules.
Video analytics can also be used to monitor the accumulation of snow, and be configured to trigger an alarm if the level of accumulated snow crosses a certain threshold value. This helps personnel make informed decisions about snow removal and general maintenance.
Moving on to traffic signals, dynamic signalling is a process used by traffic operators when the flow of traffic is variable over a certain period of time. This means that the signals function on a time scale that is determined by the present flow of traffic. Naturally, this is one of the most-affected areas in snowy conditions. Traffic operators can make use of video analytics to more efficiently regulate traffic through dynamic signal timings, and prevent congestion.
Emergency Response Management
Video analytics can be used to improve the functioning of emergency services, and ensure fast deployment when needed.
Video analytics, when integrated with emergency services, allows for speedy response at the scene of accidents or injuries - thereby reinforcing safety standards during less-than-ideal weather conditions.
Pedestrians, cyclists, and other VRUs (Vulnerable Road Users) are often neglected in the big picture that is traffic management. However, they are equally important and especially in bad weather conditions when both visibility and navigability are compromised.
Using video analytics can help traffic personnel keep a better eye on the situation, make the necessary arrangements for aid, and respond in a timely manner.
Ski Slope Analysis
People flow analysis is an intrinsic part of crowd management. While video analytics finds it use in many different kinds of people flow analysis, we are talking here of the specific event of skiing and why video analytics plays an important role in optimizing and securing the site.
Video analytics can be used to monitor individual and collective skiers, and ski lifts. This is especially important for guaranteeing the safety of all those who partake, prevent injuries, and ensure that any accidents are quickly detected and attended to.
This video is a visual rendition of Isarsoft Perception being used to monitor and analyze skiers on a ski slope.
How does Isarsoft Perception help?
Isarsoft Perception can be used to mitigate the bad effects of snowy weather. In the snow (or sleet), drivers and traffic personnel have a hard time monitoring individual vehicles, as well as the whole traffic flow. With Isarsoft Perception's reliable analytics platform, the traffic flow can be consistently monitored - with specific functions such as measurement of flow and density via the creation of lines and zones.
Users can utilize heat maps (read more about Isarsoft Perception's heat maps here) to measure and monitor specific KPIs such as speed, dwell time, trajectory, path, and position. These are built so to visualize large volumes of datasets, and to ensure a quick response time.
Individual vehicles and roads can also be monitored as per requirement, in addition to detection of rule violation and unruly driving.
The same is true of people flow analysis. Snow renders pedestrians more vulnerable to accidents and injuries, in addition to potentially worse consequences of inadequate crowd management. With Isarsoft Perception, users can detect people, measure people flow, and keep track of KPIs such as occupancy, speed, and dwell time.
This video exhibits how Isarsoft Perception can be used to detect, measure, and monitor traffic in low visibility conditions.
The above video shows a highway with heavy traffic, in the snow. Isarsoft Perception can be used to measure, monitor, and assess the flow of traffic in the snow, so as to prevent congestion, bottlenecks, and accidents.
Future Trends and Innovations
Integration with Weather Data
Weather and the traffic and transport industries are inextricably linked. Who, for example, has not had a train getting cancelled because of a snowstorm? The future of video analytics promises seamless integration with predictive weather data to avoid just that.
This will equip traffic/transport operators to have a better grasp over the situation as it unfolds, save commuters both time and money, and work towards improving the commuter experience in snowy conditions. Of course, this applies to bad weather in general and how a sudden squall of unanticipated rain or snow can halt normal life for longer than necessary.
Additionally, with integrated weather information, users will be able to create a historical database for the future and use it as a reference point.
Advancements in Image Processing
Image processing is expected to further improve, and allow users to detect objects in very low or no-light conditions. The reason this is crucial is owing to accidents or injuries that happen in snowy weather conditions. While current image processors boast an accuracy of 95-98% on average, there is still a certain threshold beyond which their detection may fail. It is in these cases that a stronger, more accurate image processor is required.
In cases of a vehicular or a skiing accident, it is imperative that the detection be accurate and the response be timely. In order for the latter to happen, the former has to be true. Reducing the impact of bad weather on video analytics is a goal that is being worked toward.
More about Isarsoft
With Isarsoft Perception, your camera systems become part of your business intelligence. Whether the goal is to increase efficiency, customer satisfaction or safety, Isarsoft Perception provides the insights needed for informed decisions.
Contact us, to learn more about how to turn security cameras into intelligent sensors.
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