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REFERENCE ARCHITECTURE

University AI Lab.
40-Seat AI Lab with Shared GPU Server.

For: AICTE / Universities / Engineering Colleges / Schools

Complete 40-seat AI/ML lab infrastructure with student dev kits, faculty workstations, and shared GPU training server. Single PO, single vendor. NEP 2020 and AICTE aligned. Pre-loaded with 50+ guided projects across computer vision, NLP, and robotics.

Architecture Overview

University AI Lab — System Architecture

A turnkey AI lab where every student gets a Jetson Orin Nano dev kit for hands-on edge AI development — computer vision, NLP, robotics, and generative AI. Faculty workstations provide model development and courseware creation capability. A shared GPU server enables batch training jobs and multi-student model experimentation. The entire lab comes pre-loaded with 50+ guided projects, datasets, and a curriculum mapped to NEP 2020 outcomes.

40 students + 2 faculty + 1 shared GPU server
Deployment Scale
Real-time inference on student kits (< 50ms per frame)
Edge Latency
Self-contained lab — operates without internet for core functionality
System Availability
All student data and models stay on-premises
Data Sovereignty
Network Topology

How the tiers connect

Student Workstation Tier

Each student gets a Jetson Orin Nano dev kit connected to a monitor and peripherals. The kit runs real-time inference locally — students can train small models, run object detection on live camera feeds, and deploy edge AI applications without waiting for server time.

Faculty & Management Tier

Faculty workstations provide higher compute (Orin NX) for model development, courseware creation, and live demonstration. Faculty can monitor student progress, review submissions, and manage lab resources through a web dashboard.

Shared Training Server

The AGX Orin GPU server runs JupyterHub for multi-student training jobs. Students submit training experiments via the LAN — the server queues and executes them, making GPU compute available to the entire class without per-student GPU investment.

Bill of Materials

Complete BOM — every component specified

All components are RDP-validated, GeM-listed, and available as a single-vendor procurement package. Quantities shown are for a typical deployment — contact us for exact sizing.

Component Platform Specifications Qty Role
Student AI Dev Kit NVIDIA Jetson Orin Nano (67 TOPS) 8GB RAM, 128GB microSD, USB camera, GPIO breakout, carrying case, power adapter 40 Hands-on AI development — image classification, object detection, NLP, robotics projects
Student Monitor + Peripherals 22" FHD monitor, keyboard, mouse 1080p IPS, VESA mount, USB keyboard/mouse, headphones 40 Student workstation display and input
Faculty Workstation NVIDIA Jetson Orin NX (100 TOPS) 16GB RAM, 512GB NVMe, dual display output, full JetPack SDK, 27" 4K monitor 2 Model development, courseware creation, student project review, live demo
Lab GPU Server NVIDIA Jetson AGX Orin (275 TOPS) 64GB RAM, 2TB NVMe, 10GbE, shared Jupyter Hub, multi-user training server 1 Batch model training, shared datasets, student experiment server, model repository
Lab Network Switch Managed Gigabit switch 48-port GigE, 4× 10G SFP+ uplinks, VLAN, QoS for training traffic 1 High-speed LAN connecting all kits to GPU server and faculty workstations
Lab Projector / Display Interactive 75" display or laser projector 4K, HDMI/USB-C, touch-enabled (display) or 5000-lumen (projector) 1 Live demo, code walkthrough, student presentation
Robotics Accessory Kit (optional) Robot chassis + sensors 2WD/4WD chassis, LIDAR, IMU, servo motors, ultrasonic sensors, ROS2 compatible 10 (shared) Robotics projects — autonomous navigation, SLAM, obstacle avoidance
Pre-loaded Curriculum RDP VIDYA.AI courseware 50+ guided projects, datasets, Jupyter notebooks, assessment rubrics, faculty guide Site licence NEP 2020-aligned AI/ML curriculum across 4 semesters
Indicative Pricing: Indicative range: ₹35–55L per 40-seat lab (all-inclusive) depending on monitor spec and optional robotics kits. All components are GeM-listed for government procurement. Contact sales@rdp.in for a detailed quotation.
Deployment Requirements

What you need to deploy

Power

Lab total: ~3 kW (40 kits × 25W + faculty + server + peripherals). Standard 15A power circuits sufficient.

Cooling

Standard air-conditioned lab (20–28°C). No special cooling required — all devices are low-power.

Connectivity

Gigabit LAN within lab (required). Internet (optional) — for software updates, cloud dataset access, and remote support.

Space

Standard 40-seat computer lab (80–100 sq.m). Each desk needs 1 power socket and 1 LAN port.

Installation

RDP provides lab design, network cabling layout, hardware setup, software pre-loading, curriculum installation, and 2-day faculty FDP (Faculty Development Programme)

Compliance & Certifications

Standards and regulatory alignment

  • NEP 2020 AI/ML curriculum alignment
  • AICTE model curriculum compatible
  • UGC LOCF compliant
  • NAAC/NBA documentation support
  • GeM-listed (single PO procurement)
  • Make in India certified
  • VIDYA.AI education partner programme

Ready to deploy University AI Lab?

Share your scale, site requirements, and timeline. We’ll customise this reference architecture to your exact deployment — from BOM to commissioning.

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