Support for school management and exam integrity

Detection of the presence and use of cell phones in environments where they are prohibited for safety, quality or confidentiality reasons — such as production lines, machine operation, cleanrooms, exams and areas with sensitive information.

How it works

1. 1The detector identifies people and cell phones in each frame.
2. 2The phone is associated with the nearest person (hands/face).
3. 3The occurrence is recorded per tracked person, with accumulated usage time.

Benefits

• Reduces distraction-related accidents.
• Enforces information security policies.
• Objective records for feedback and training.

Support for proctoring tests, civil service exams and certifications: the AI follows each candidate and flags suspicious behavior — prolonged glances at a neighbor's paper, phone use and candidates getting close — marking the exact moment for review by the proctor.

How it works

1. 1The pose model estimates each candidate's head orientation.
2. 2An object detector looks for phones near the hands and face.
3. 3The distance between heads indicates proximity/communication.
4. 4Each occurrence gets a timestamp with an image for auditing.

Benefits

• One proctor supervises more rooms with AI support.
• Objective evidence for appeals and annulments.
• Proven deterrent effect of smart surveillance.

AI model trained to recognize facial expressions associated with emotions — happiness, sadness, fear, disgust, surprise, anger, contempt and neutral. It measures in real time how customers, students and audiences react to products, service, classes, storefronts and presentations.

How it works

1. 1The YuNet detector locates the faces in each frame.
2. 2The HSEmotion model (trained on the AffectNet dataset) classifies 8 emotions with probabilities.
3. 3Readings are smoothed over time per person to avoid fluctuations.
4. 4A satisfaction (valence) index summarizes the audience's mood minute by minute.

Benefits

• Objective emotional feedback, without questionnaires.
• Identifies the moments and products that generate the most delight (or frustration).
• Complements NPS and surveys with continuous, anonymous data.

Face enrollment and recognition for access control, event check-in, attendance tracking and personalized service. An enrolled face becomes a numerical signature (embedding) compared in milliseconds with every face detected by the cameras.

How it works

1. 1The face is enrolled from a photo or the camera (name and profile).
2. 2The SFace network generates a 128-dimensional vector that represents the face.
3. 3Each detected face is compared with the database by cosine similarity.
4. 4Identified and unregistered people trigger different events (welcome × alert).

Benefits

• Access and check-in without queues, cards or badges.
• Personalized service — the salesperson knows who has arrived.
• Auditable access log.

Automatic, anonymous people counting: entries and exits through a virtual line, real-time occupancy, unique visitors, average dwell time and a heat map of the most visited areas — turning cameras into an audience sensor for operations and marketing decisions.

How it works

1. 1Each person is detected and tracked with an anonymous identifier.
2. 2Crossing the virtual line defines an entry or exit.
3. 3Accumulated positions form the circulation heat map.
4. 4Reports by hour, day, week and store support staffing, layout and campaigns.

Benefits

• The store's real conversion rate (traffic × receipts).
• Staff scheduling aligned with peak traffic.
• Product layout and display guided by the heat map.
• Capacity control for safety and fire code compliance.