The Problem: Limited Visibility into Learning Dynamics

Public schools often struggle with large class sizes, suboptimal teacher-student ratios, and insufficient tools to track engagement in real time. In Pimpri Chinchwad, classroom activities were being monitored only by teachers, leading to inconsistencies in gauging student attentiveness and participation. Data on teacher efficiency, time spent on instruction, and resource use were not being captured systematically. These challenges created significant blind spots in school governance and curriculum delivery.

AI as a Solution for Holistic Monitoring

To address these gaps, PCMC piloted an artificial intelligence-based education analytics system across 18 classrooms in 3 municipal schools. The solution deployed AI software to analyze real-time video feeds from two classroom-installed cameras—one focused on the teacher’s board and another on students’ desks.

The system monitored various indicators of student behavior, such as attention span, emotion, movement, and punctuality. It also tracked teacher performance, including active teaching time, interaction with students, and use of learning tools. By generating behavior-based dashboards, it enabled headmasters and supervisors to intervene when needed and promote consistent instructional quality across schools.

Policy Relevance and National Alignment

This initiative aligns with key objectives of the National Education Policy (NEP) 2020, which emphasizes the use of technology to improve learning outcomes, enable teacher training, and support school leadership. It also complements Digital India by promoting smart classrooms and Viksit Bharat @2047 by fostering transparent, accountable, and adaptive public services.

Moreover, by proposing a decision support system (DSS) based on behavioral analytics, the project reflects a broader push towards evidence-based education management and the personalization of student learning paths in resource-constrained environments.

Impact on Schools and Stakeholders

Despite its limited scale, the pilot has yielded promising outcomes:

• Student engagement metrics (attention and emotional data) were successfully captured, providing baseline insights for future interventions.
• Teacher behavior became more focused due to camera-based accountability, resulting in improved classroom discipline and more structured interactions with students.
• Supervisory capacity was enhanced, allowing school heads to give targeted feedback and initiate timely corrective actions.

The initiative also created awareness among stakeholders—including the education department and civic administrators—about the potential of AI to fill systemic monitoring gaps that manual methods cannot address.

Challenges and Key Learnings

Implementation faced delays due to the COVID-19 pandemic and its associated restrictions, such as students and teachers wearing masks, which inhibited the facial recognition component. Other hurdles included poor internet infrastructure and the lag in data upload to the central server, which limited real-time analytics.

However, valuable learnings emerged:

• Real-time image processing may be replaced with scheduled frame sampling to reduce server load.
• Future iterations could include edge computing or local servers to decentralize data storage and analysis.
• Infrastructure readiness—especially high-speed connectivity—must precede digital education reforms for optimal impact.

Laying the Foundations for Smarter Schools

Pimpri Chinchwad’s AI-driven classroom analytics system represents a frontier innovation in public education. By integrating artificial intelligence into municipal schools, the city has initiated a shift from anecdotal teaching reviews to measurable, behavior-based insights. While the pilot remains small in scale, its vision of enabling data-informed decision-making for both administrators and educators is scalable and replicable across urban India.

As the education sector looks toward hybrid and technology-integrated learning models, this initiative offers a robust example of how even local governments can harness AI to enhance accountability, improve learning environments, and build smarter schools for the future.