Predictive analytics in video surveillance. Principles, objectives, opportunities

Predictive analytics. Principles, objectives, opportunities

Can a video surveillance system be self-learning? How real can be the transition to a fundamentally new stage in development of the IT market? These questions were asked by developers and users several decades ago, and today predictive analytics in video surveillance is a reality of our life. It is used to improve security and increase the efficiency of business processes. Want to know more? Read on.

What is predictive analytics?

Predictive analytics can be defined as a set of methods for analyzing data obtained from a video sequence and available database of past events. The predictive video analytics algorithm is able to predict further events.

The system “learns” on the basis of behavioral styles, using technologies for recognizing emotions, objects, recording the fact of deviation from the given parameters, for example, movement route (transport, various objects, people).

As a result of a comparative analysis of the event, the system notifies the operator of the need to make decisions to prevent an unwanted incident.

CONCLUSION: predictive video analytics allows to reduce the load on the operator due to algorithms for tracking situations at facilities and identifying alarm triggers in automatic mode.

Three pillars of predictive analytics

Predictive analysis in video surveillance is based on three pillars:

  1. Collection of information
  2. Exploratory data analysis
  3. Modeling the future situation.

Areas of application

Today, predictive video analysis is used in the following areas:

  • urban infrastructure, in particular in a safe city system;
  • transport sector, especially in the field of license plate recognition;
  • medicine (improving the efficiency of diagnostics);
  • heavy industry (control over the implementation of technological processes and compliance with safety regulations);
  • agro-industrial sector;
  • private business in order to control labor processes and quality of service.

Goals and objectives

Two global goals of predictive analytics:

  1. Ensuring safety:
  • at large production facilities due to the introduction of automated control over equipment and work of employees;
  • at public facilities (stadiums, metro, airports/train stations, shopping centers, retailers) through the introduction of modules for crossing lines and transferring objects. They are 100 percent accurate.
  1. Increase in the efficiency of business tasks:
  • cost reduction;
  • reducing the volume of scrap in production;
  • optimization and automation of processes;
  • control over the performance of official duties and regulations;
  • control over the quality of service and its improvement;
  • control of empty shelves;
  • forecasting the load of transport and roads, as well as changing the cost of toll roads;
  • automatic assessment of the road surface quality and forecast of repair.

Solutions that work in the Russian Federation

According to a report by the international analytical agency Forrester, the global predictive analytics market will grow by 21% annually until 2021. The basis of forecasts is an increase in consumer requests and indicators of orders for the corresponding equipment and solutions.

But it is difficult to say that the Russian market segment has signs of stability and growth. The fact is that historically Russia is late with the development of the IT market by about 20 years.

Currently, predictive video analytics and similar solutions with signs of artificial intelligence are being tested in the public sector, in the transport sector and among large retail chains (Lenta, X5 Retail Group). In 2020, it is worth noting a large number of requests from manufacturing enterprises.

In the event that you are interested in affordable intelligent video analytics, pay attention to the Faceter service. The software works on the basis of mobile devices, does not require special skills to install the system and has affordable prices. And the efficiency of the used computer vision algorithms is confirmed by the University of Washington (USA). Details on the website https://faceter.cam/en

Conclusion

Obtaining information at the initial stage of an event (more often undesirable or dangerous) helps the operator to quickly respond to the situation. This allows you to competently and timely act in order to prevent an undesirable event. This is the point of predictive video analytics.

Александр Вебер

Alexander Weber

Specialist in video surveillance, video analytics, cloud storage systems. Consultant on the integration of video surveillance systems and tools in various business sectors. Over 10 years of industry experience.

See also