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Comprehending Workplace Surveillance with Video Analytics

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Overview of the Case Study - Incident

Most workplaces remain open 24*7 to serve their customers anytime and provide them value. Therefore employees and visitors always visit there, some for their daily work and some for interviews and consulting. It makes that environment busy, chaotic, un-enjoyable, and unsafe because it may be possible that an unknown person visits with wrong intentions. They can harm the infrastructure as well as the person. Therefore Workplace surveillance is necessary.

Investigation with Workplace surveillance

One of the organizations’ significant challenges is to identify, track and detect those anomalies and persons. Some other challenges of workplace surveillance are :
  • Identification: Organizations are not able to identify known or unknown people as a lot of people visit the workplace.
  • Paperwork: Need a lot of paperwork is to handle their entry record. Manual processes are not only inefficient but also increase security risk and costs.
  • No Anomaly Detection: Organizations are not able to detect any anomaly at workplaces.
  • No Historical Tracking: Organizations not able to track or map if a person is visiting again and again.

Camera-based intelligent video analytics open the minds to widespread possibilities via video streams. Source: Intelligent Video Analytics

Incident Response

To solve these problems, a solution is necessary that makes workplaces productive and safe using AI and video analytics. The system should detect a person; based on appearance; it recognizes the visitors or regular employees. Then accordingly, monitor access management, behavior analysis, anomaly detection, and alert management to make the system more reliable. It should also analyze crowd and presence using self-learning analytics. It should also monitor suspicious activities and send an alert to the respective authorities for the actions if encountered. Overall, the system should monitor the whole process using video analytics.

How can XenonStack Help?

Xenonstack provides a solution that will cover the following scenario to solve a problem for workplace surveillance : Real Time Video Analytics Covering those scenarios, it will allow monitoring the following cases:

Boundary Breach Detection

    • Virtual Boundary: It allows for tracking the entry and exit of people in a particular area. Thus, users can track the number of visitors, their time of visits, and the duration of their stay there. It allows interlopers to access those areas.
    • Forbidden Area Violation: The system generates an alert a person doesn’t have access to a certain area but enters there. It detects real-time violations and malicious activities, thus enhancing the safety and security of the place.

Theft Analysis

    • Theft Alert: Systems always track the inventory of a workplace. If it detects any object's movement at an abnormal time, it alerts the manager.
    • Loitering: The system keeps track of passers-by and records their time they spend in monitored zones. The system generates an alert when more than usual time is spent by a passer-by at the same spot.

Anomaly Detection

    • Suspicious Movement Analysis: If anyone spends extra time in a specific location, the system will raise the alarm. Thus detect any suspicious activity before it occurs on-premises.
    • Abandoned Object: The system can identify unattended stationary objects, thus detecting threats of cases where objects are left behind with wrong.
    • Fire Alert: CCTVs or smoke detectors only detect smoke or fire. But they respond only to smoke or flames after the fire has already begun.
Thermal imaging cameras can see through smoke and have the exact temperature and location of hotspots.
Click to explore AI-based Video Analytics and its Challenges


    • Bottleneck Analysis: The system may detect the crowded place immediately and alert the organizer. For taking immediate action to make the environment peaceful by reducing the wait time.
    • Entry/Exit Counts: Using a feature-rich camera placed at different locations, users can keep track of the persons and an object entering or exiting the premises.
    • Traffic Queueing: The system detects the traffic of people and vehicles at entry gates. And monitor their behavior and early detect the situation before it becomes more cumbersome.

Trip Tracking

    • Path Analysis within an Area: The system keeps track of the visitor’s journey to monitor their activity always.
    • Presence Distribution Map: Analysing the location and people density in various locations a different times. Users can make decisions regarding scheduling the break and the work timing of people.

Read more about Video Analytics with Brief Use-Cases

Questions to Discuss for Workplace Surveillance

Still, some questions come in customer minds: “ How the system will perform”, “How it tracks a person?”, “When will it generate an alert?”, To answer all these questions, we will discuss a case study for workplace surveillance that will answer all user questions and explain how the system works for an unauthorized person’s journey from entry to exit.
  • How does the system prevent the entry of unknown people? How does it get to know that a person is unknown?
The system detects a face and identifies whether a person is authorized or unauthorized. By matching it with already recorded faces from a database when a person visits a workplace. If a person is unknown, it generates an alert at the entry and thus stops entry.
  • Okay, I got to know how the system will detect and prevent the entry of unknown people. But what if a visitor or interviewee comes for the first time? How does the system allow them to come? How does that person get an entry? Whether he/she will be able to come inside the workplace or not?
If the person is unknown, then it starts with Access Management. Meaning it will give temporary access to him/her.
  • As answered in the previous question, that system will give access to them. What is necessary to give access?
At the entry time, the system gives temporary permission with some information like Purpose, Name, Floor, Department, Concern Person, Time Slot, Phone Number.
  • How does the system get to know that the access they were given to is the right person? Because it may be possible that the person is not coming for an interview, he can be the wrong person?
An alert will be sent to the organization about the meeting of a temporary person. So the organization will get to know whether that person has an invitation or not.

According to the Artificial Intelligence Global Surveillance index, at least 75 out of 176 countries globally are actively using AI-based surveillance technologies. Source – How AI Is Making An Impact On The Surveillance World
  • Okay, As discussed in the previous question, a person will be allowed entry for some defined time. How will the system get to know whether a person leaves at the correct time or not?
The system will continue monitoring a person; If a person exceeds its time limit in case of an unauthorized person, an alert will be generated to a respected person and the organization.
  • It is also possible that the person that entered the workplace went to the wrong location by mistake or intentionally. Or it may also be possible that person is harming another person or ruining infrastructure. How may the system get to know about that?
After giving entry, record his path and behavior. So if a person is going to a restricted area or doing any suspicious activity, an alert will be sent to the respective organization.
  • Are these all cases possible for authorized because he/she may also do the same?
Yes, the system also monitors the path of authorized people. And in all of the possible scenarios discussed above, an alert will be generated to the respective organization.
  • A person may be visiting again and again, but he/she is not a regular person, so he/she has to register themselves? How did the system get to know?
When an unknown person visits a workplace, his/her data will be saved in the database. So that it can map temporarily accessible people on his/her next entry.
  • When does the system stop tracking?
The system will successfully exit and close the case of a particular person when he/she will leave the building. Workflow Productivity Measurement with Video Analytics


The workplace surveillance solution will track, manage, check and improve employee productivity to keep the workplace safe from theft, sabotage, and malicious activities.

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Comprehending Workplace Surveillance with Video Analytics

Enterprise AI

Comprehending Workplace Surveillance with Video Analytics

Overview of the Case Study - Incident Most workplaces remain open 24*7 to serve their customers anytime and provide them value. Therefore employees and visitors always visit there, some for their daily work and some for interviews and consulting. It makes that environment busy, chaotic, un-enjoyable, and unsafe because it may be possible that an unknown person visits with wrong intentions....