Analysis of audience demographics is basic in modern businesses, especially those making decisions using data. In our study, we will show you how TAI was able to create a high-level AI system for the identification of age and gender using AI, which engages in analyzing visual data to present valuable demographic information. This tool functions as a real-time age & gender detection AI.

Developed through the use of facial recognition AI technology and deep learning algorithms, the system is capable of automatically analysing demographic data through the use of artificial intelligence with no human intervention required. Through the use of machine learning algorithms for age and gender recognition in conjunction with an analytic platform infused with artificial intelligence, analysis is possible in a matter of seconds and with a high level of predictive accuracy.

Problem Statement

The client required a reliable system of real-time analysis of demographic information without having to conduct any surveys and gather data manually. The current methods were not only inaccurate but could not be scaled up in any efficient manner. Such was the level of disparity in AI solutions related to the prediction of age and gender, where there was no standardised AI solution.

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Challenges

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There existed a few technology and process-related issues:

  • Inaccurate demographic information gathered using conventional approaches
  • Insufficient real-time computer vision for the detection of age and gender
  • Large latency values in data processing
  • Integrating facial recognition into the process of profiling users
  • Poor insights due to the lack of predictive analytics AI usage

These requirements brought about the necessity for a scalable and accurate artificial intelligence system for human attribute recognition.

Solutions

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TAI designed a robust solution using modern computer vision and AI technologies.

Advanced Facial Recognition and Computer Vision
It incorporates facial recognition with an age and gender-detection module using computer vision in its analysis processes for higher accuracy in its visual inputs.

Demographic Models Based on Deep Learning
Through the application of deep learning demographic analysis, the system can enhance its predictive levels through constant adaptations to different data sets.

Real-Time AI Analytics Platform
This is achieved through a scalable artificial intelligence analytics platform that processes information in a live setting.

Seamless System Integration
The AI-based identification tool was developed to be integrable with current applications effortlessly to enable overall AI analytics for demographic data in business systems.

Our Team

  • Project Leader (BrSE)
  • ML Engineer
  • Back-end Engineer
  • Devops Engineer

SDLC Stages

  • Requirement definition and specification formulation
  • Design
  • Development and implementation
  • Infrastructure construction
  • Preparing the dataset
  • Model evaluation
  • Model deployment

Technical Stack

  • Python
  • PyTorch
  • Sagemaker
  • TensorFlow
  • OpenCV
  • Transformers
  • Numpy
  • Pandas
  • Matplotlib

Tools & Technologies Used

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Results & Outcomes

The implementation of the age and gender identification system using AI brought excellent results. The system was able to give the client real-time demographic analysis with high accuracy, and this helped them make faster and more informed decisions.

The use of automated age and gender detection AI meant that there was no manual processing of data, thus cutting operational costs to a significant extent. The real-time age and gender detection system was able to process high volumes of data without compromising performance. Improved AI demographic analysis enhanced trend identification and audience segmentation by stakeholders.

Further, the incorporation of predictive analytics AI increased the efficiency of long-term planning with the ability to provide accurate demographic projections. In summary, the system is now a scalable and smart AI for predicting age and gender.

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Case Studies

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