The Lab for Cyber Threat Intelligence at VIT, Chennai was established with the support of the Department of Science and Technology (DST) under the Fund for Improvement of Science and Technology (S&T) Infrastructure (FIST) programme. It is dedicated to pioneering advancements in cybersecurity. The lab’s multifaceted objectives are designed to enhance research capabilities, develop innovative cybersecurity solutions, foster education and training, promote industry collaboration, and support national security. These comprehensive objectives aim to create a significant impact on both national and global cybersecurity landscapes.

Duration: 2022 – 2027

Fund Received: 76 Lakhs

Fund for Improvement of S&T Infrastructure

NVIDIA H100 80GB PCIe 5.0 x16 Deep Learning Server

Key Features of 2 x NVIDIA H100 80GB PCIe 5.0 x16:

NVIDIA H100 80GB PCIe 5.0 x16 Overview

The 2 x NVIDIA H100 80GB PCIe 5.0 x16 setup consists of two NVIDIA H100 GPUs, each with 80GB of memory, using the PCIe 5.0 x16 interface for high-speed communication with the system.

NVIDIA H100 GPU:

The NVIDIA H100, based on NVIDIA’s Hopper architecture (released in 2022), is designed for high-performance computing (HPC), artificial intelligence (AI), and machine learning workloads. It provides massively parallel processing capabilities and optimised performance for large-scale, compute-intensive tasks like training deep neural networks and performing complex simulations.

80GB of High-Bandwidth Memory (HBM3):

Each NVIDIA H100 has 80GB of HBM3 memory, which allows for fast storage and access to data processed by the GPU. This large memory capacity helps handle massive datasets, complex AI models, and large-scale AI training efficiently, reducing data bottlenecks in GPU-accelerated tasks.

PCIe 5.0 x16 Interface:

The PCIe 5.0 (Peripheral Component Interconnect Express 5.0) standard offers significantly higher data transfer rates than previous generations.

• PCIe 5.0 x16 ensures each GPU uses a 16-lane connection, enabling high-bandwidth communication between the GPU and the rest of the system (CPU and memory).
• This interface reduces latency and maximises GPU performance, supporting faster data throughput.

Significant Areas of Research in Linux Servers

1. AI and Deep Learning (DL) Models

• Training Large Language Models (LLMs): The H100’s power and memory enable the efficient training of massive models like GPT and other transformer-based architectures.
• Reinforcement Learning: The H100 accelerates RL training, used in robotics, gaming, autonomous vehicles, and decision-making systems.
• Vision and Natural Language Processing (NLP): Researchers use the H100 for computer vision tasks (e.g., object recognition) and NLP applications (e.g., text generation and sentiment analysis).

2. High-Performance Computing (HPC)

• Scientific Simulations: The H100 is used for simulating complex physical phenomena, such as weather patterns, climate modelling, and molecular dynamics simulations.
• Quantum Computing: The H100’s computational power aids in quantum computing research and simulations.
• Computational Chemistry: The H100 accelerates research in quantum chemistry, material science, and drug discovery.

3. Autonomous Systems and Robotics

• AI for Autonomous Vehicles: The H100 supports real-time decision-making and sensor data processing for self-driving cars.
• Robotic Motion Planning: The H100’s tensor cores accelerate object detection, motion planning, and autonomous navigation in robots.

4. Generative AI and Creativity

• Generative Models: The H100 enables research into GANs (Generative Adversarial Networks), diffusion models, and AI-generated creative content.
• AI-Assisted Design and Manufacturing: The H100 accelerates AI-driven design tools for architecture, engineering, and industrial design.

5. AI Hardware Optimization

• Energy Efficiency in AI Workloads: The H100 supports energy-efficient AI models, optimising power consumption in data centres.
• GPU Performance Tuning: Researchers work on optimising GPU hardware (e.g., memory management and multi-GPU setups) to enhance real-world AI performance.

6. Data Analytics and Big Data Processing

• Distributed Systems: The H100 is used for large-scale data processing in fields like finance, healthcare, and social media.
• Graph Analytics: High-performance graph processing algorithms (e.g., for social networks and biological networks) benefit from the H100’s high throughput.

7. Security and Cryptography

• AI in Cybersecurity: The H100 accelerates AI-powered cybersecurity, detecting and mitigating cyber threats using anomaly detection and pattern recognition.
• Cryptography and Blockchain: The H100 optimises cryptographic computations in blockchain, cryptanalysis, and security protocols.

8. Edge Computing and AI Deployment

• Edge AI: The H100 helps deploy AI models on edge devices, enabling real-time inference with low-latency processing.
• IoT and Smart Devices: The H100 contributes to AI-powered IoT systems, with applications in smart cities and industrial automation.

9. Machine Learning Infrastructure and Cloud Services

• AI Model Deployment at Scale: The H100 powers cloud-based AI infrastructure, supporting massive model deployments.
• Federated Learning: The H100 scales federated learning frameworks, ensuring data privacy in decentralised AI training.

10. Cloud Gaming and Real-Time Rendering

• Ray Tracing and Rendering: The H100 supports real-time rendering for cloud gaming and cinematic production.
• AI-Powered Content Delivery: The H100 enhances graphics processing for AI-driven content delivery and game streaming.

11. AI-Driven Healthcare

• Medical Imaging: The H100 accelerates deep learning models for medical image analysis (CT, MRI, X-rays), improving diagnostic accuracy.
• Personalised Medicine: The H100 supports AI research in genomics, enabling personalised treatment plans and drug discovery.

Our Vision:

At VIT Chennai, the ADAPT Lab is founded on the twin pillars of education and research. We envision a dynamic and transformative environment where students gain not only a strong academic foundation in Unmanned Aerial Systems (UAS) but also engage in innovative research that pushes the boundaries of aerial technology. Our lab aspires to be a center of excellence that empowers future-ready engineers and researchers to shape the future of drone technology.

Infrastructure & Facilities:

The Drone Lab is equipped with state-of-the-art tools and technologies supporting educational activities and high-impact research in unmanned aerial systems. Our facilities are designed to support the complete lifecycle of drone development, from ideation and prototyping to testing and real-world deployment.

• Drone Assembly & Maintenance
• Software Simulation & Testing Suite
• Flight Control & Communication Station
• Power & Charging Station
• Payload & Sensor Integration Bench
• Electronics & Soldering Station
• Outdoor fly zone

Available UAS:

1. Quadcopter:

Purpose: This quadcopter is suitable for projects such as obstacle avoidance, path planning, an indoor navigation system, etc.

2. Quadcopter:

3. Octocopter:

Purpose: This octocopter is suitable for projects with heavy payloads, such as aerial surveillance and cinematography, package delivery, and precision agriculture applications, such as spraying.

All these drones are capable of manual/semi/fully autonomous flight.

Key Activities and Research Areas:

• Training programmes on Drone design and development
• Drone Piloting and Operation Training
• Drone Hardware and Software Development Workshop
• Autonomous Navigation and Control Systems
• Sensor Integration and Payload Development
• Environmental Monitoring and Precision Agriculture
• AI integration with UAV
• Drone racing

Big Data Analytics Lab is utilized by postgraduate students who are pursuing the specialization course in Big Data Analytics Lab. The students get an opportunity to practice & explore different service models of the Big Data Analytics Lab. The major focus is on training students in Open Source technologies and toolkits to develop real-time and industry-related applications. A wide range of open source projects is hosted at the Laboratory including desktop applications, browsers and programming language compilers/interpreters.

AB1 208 Lab

CASE tools known as Computer-aided software engineering tools is a kind of component-based development which allows its users to rapidly develop information systems. The main objective of case Laboratory is the automation of the entire information systems development software life cycle process using a set of integrated software tools, such as modeling, methodology and automatic code generation.

613 Lab

Cloud Computing Laboratory is utilized by post graduate students who are pursuing the specialization course in Cloud Computing and Big Data Analytics. The students get opportunity to practice and explore different service models of cloud computing. The cloud infrastructure and platform has been established to give in-depth knowledge about each of the cloud services. We explored private cloud, public cloud and open source providers. The students are able to create, deploy, and configure the virtual machines for different types of virtualization techniques. VIT Chennai campus has MoU with IBM Solutions Company. We established IBM software Excellence and utilizing the IBM tools for Laboratory sessions.

AB1 206 Lab

Cyber Physical Systems Laboratory

Ideas to Proof of Concepts

Vision

Engineering is Imagineering. The vision of Cyber Physical Systems Lab is to enable VIT student community for building their ideas into prototypes in two ticks. Such proof of concepts (PoCs) can strengthen the student’s thought process and confident level in parallel thinking for connecting engineering concepts with real-time problems which will end up with the solutions. Therefore, the students can gain knowledge in understanding industrial problems, research and development laboratory exposure and system development in the VIT Campus itself. Importantly, such environments can create an opportunity to develop the indigenous technology products of our nation.

Cyber Physical Systems Lab is equipped with the virtual instrumentation hardware systems and software tools for the fastest implementation of PoCs. An architecture of a basic embedded system is given in Figure 1.

1. CPS lab facilitates the infrastructure for developing proof of concept to the VITians using sensors, electronic circuit modules, embedded system technologies, and recent Internet-of-Things. Example: Industrial standard electrostatic discharge workspace, reference electronic circuit modules, mixed signal oscilloscopes, digital power supplies, and high-performance computing facilities.
2. To understand the basics of Embedded system concepts, CPS Lab is equipped with generic Embedded system evaluation boards like Arduino, National Instruments Engineering Laboratory Virtual Instrumentation Suite (NI ELVIS) hardware system and Embedded Device with reconfigurable Input/Output (myRIO).
3. To understand the concepts of sensors, actuators, and simple motor speed control systems, CPS lab provides sensors for measuring various modalities like distance, pressure, etc.., actuators like motors and relays, controls, and simple systems. Example Ultrasound sensors, Infrared LED, strain gauge, NI ELVIS board and daughter cards.
4. To provide hands-on experience in design and developments of embedded systems and internet of things technologies for generating human resources in this field.
5. CPS Lab is also open for discussing real time problems with industrial experts for providing solutions to the challenges and issues in Industries.

Images of CPS lab and Events

Engineering embodies the art of imagination and innovation. The overarching mission of the Cyber Physical Systems Lab is to empower the student community at VIT to translate their visionary concepts into tangible prototypes with remarkable efficiency. These proof of concepts (PoCs) serve to fortify students’ cognitive agility and self-assurance, fostering a seamless integration of engineering principles with real-world challenges, ultimately culminating in viable solutions. Consequently, students are afforded invaluable insights into comprehending industrial dilemmas, gaining exposure to research and development laboratory practices, and honing their skills in system development. Significantly, such an environment nurtures the cultivation of indigenous technological advancements.

Cyber Physical Systems Lab is equipped with the virtual instrumentation hardware systems and software tools for the fastest implementation of Proof of Concepts (PoCs) as shown below.

The CPS Lab espouses a distinct emphasis on fostering innovation and product development aimed at realizing Sustainable Development Goal 11 – Sustainable cities and communities. It provides the requisite infrastructure to VITians for conceiving proof of concepts utilizing an array of resources, including sensors, electronic circuit modules, embedded system technologies, and contemporary Internet-of-Things frameworks. Noteworthy assets encompass industrial-grade electrostatic discharge workspaces, reference electronic circuit modules, digital power supplies, and high-performance computing facilities.

To facilitate an understanding of fundamental Embedded System concepts, the CPS Lab is equipped with versatile evaluation boards such as Arduino, the National Instruments Engineering Laboratory Virtual Instrumentation Suite (NI ELVIS), and reconfigurable Embedded Devices like myRIO.

In the realm of sensors, actuators, and motor speed control systems, the CPS Lab offers an array of resources for hands-on exploration. These include sensors capable of measuring various modalities such as distance and pressure, actuators like motors and relays, as well as controls for simple systems. Exemplary assets encompass ultrasound sensors, infrared LEDs, strain gauges, the NI ELVIS board, and compatible cards.

List of IoT boards in Cyber Physical System Laboratory

A core objective of the CPS Lab is to provide students with hands-on experiences in designing and developing embedded systems and Internet-of-Things technologies, thereby nurturing a pool of adept human resources in this domain.

Furthermore, the lab boasts comprehensive support for an array of foundational IoT boards, including ESP32, NodeMCU/ESP8266, Arduino Uno, along with an extensive assortment of sensors exceeding thousands in number, facilitating the rapid prototyping of Minimum Viable Products (MVPs). This enables students to progress seamlessly from conceptualization to the realization of finished products and patenting.

The CPS Lab also serves as an avenue for engaging in discourse with industry experts, fostering collaborative endeavours aimed at devising solutions to real-time challenges and issues encountered in various industrial sectors.

Data Analytics Lab is utilized by postgraduate  students who are pursuing the specialization course in Data Analytics Lab. The students gets opportunity to practice & explore different service models of Data Analytics Lab. the students are able to create,deploy &configure the virtual machines for different types of virtualization techniques.

AB 313 Lab

Database Management System laboratory aims at facilitating and improving the usability of database concepts. Oracle 11g has installed in all systems in this laboratory. Using this Oracle 11g, students can design tables, procedures, triggers and packages. Students can develop applications using C, C++,Visual Studio 2010, .Net framework 2010 with Oracle as backend.

AB 404B

Database Management System laboratory aims at facilitating and improving the usability of database concepts. Oracle 11g has installed in all systems in this laboratory. Using this Oracle 11g, students can design tables, procedures, triggers and packages. Students can develop applications using C, C++,Visual Studio 2010, .Net framework 2010 with Oracle as backend.

AB1-614

Digital and Microprocessor laboratory aims at providing hands on session to students on digital design, 8086 Microprocessor and its interfacing and design of embedded systems using microcontrollers. The laboratory is equipped with 36 Intel Pentium systems with MASM-6.11 and Keil software enabling students to develop programs. The laboratory is also equipped with Digital trainer Kits, Microprocessor (8086) kits and Embedded (8051 and ARM) kits using which students design digital circuits, write and test assembly language programs.

AB207 Lab

Internet and Web Programming laboratory provides facilities for the students to learn web programming, design and develop web applications. Java 8 with support to run Servelet and JSP is available in the lab. Oracle 11g is installed to provide backend support for the web applications. Browsers are upgraded to support HTML 5 and recent Javascript commands. Integrated Development Environments NetBeans and MS Visual Studio 10 are also available to facilitate professional development of applications.

AB 605B Lab

This laboratory is used by the students and scholars for inventive research directions in artificial intelligence, machine learning, deep learning, reinforcement learning, explainable AI and big data analytics. This laboratory has many high-end computers that enable faster computing for various domain-specific projects. The students cultivate various developments for their internships and competitions using several software’s installed in this laboratory such as MATLAB 2021A, ANACONDA 3.6, TABLEAU and UNITY among many others.

MIDAS-Lab

This Laboratory enables the students and researchers to run experiments on multicore systems in order to evaluate the programs on performance gains. The intent is to share development techniques that are known to work effectively for multi-core processors thus resulting in reduced development costs through a shorter time-to-market and a more efficient development cycle for those employing these techniques. This Laboratory has 55 Pentium D systems.

AB210 Lab

Network Security Research Laboratory is utilized by students for HP 280G2 systems dedicated to support with fortinet firewall and develop Security related software’s. The major focus is on training students in Network based technologies and toolkits to develop real time and industry related applications.

AB 311 Lab

The Open Source Programming Laboratory is equipped with 74 Dell Optiplex systems dedicated to support and develop Open Source software. The major focus is on training students in Open Source technologies and toolkits to develop real time and industry related applications. A wide range of open source projects are hosted at the Laboratory including desktop applications, browsers and programming language compilers/interpreters. The Laboratory also makes contributions to open source community.

AB 605A

This Laboratory facilitates in developing robust applications using C, C++,Java , Perl, Python. Students can design web based applications using PHP, XAMP. Students are able to develop wireless applications using java.

AB404A Lab

This Laboratory facilitates in developing robust applications using Python, C, C++, Java and Perl. Students can design web-based applications using PHP, XAMP. Students are able to develop wireless applications using Java J2EE and J2ME Wireless kits.

AB205A Lab

This Laboratory facilitates in developing robust applications using Python, C, C++, Java and Perl. Students can design web-based applications using PHP, XAMP. Students are able to develop wireless applications using Java J2EE and J2ME Wireless kits.

AB205B Lab

The Programming Language – IV has facilitated a comprehensive set of tools that allow the students to explore different programming languages, software development methodologies, data analysis techniques, and more. The student can gain hands-on experience and apply theoretical knowledge to real-world scenarios, preparing for a wide range of careers in computer science and related fields.

A student can access a rich and diverse set of tools and software, providing opportunities to learn and work on various aspects of computer science, programming, and related fields.

Here’s a breakdown of what a student could do and learn with the installed software:

C++ (Dev. C++, Turbo C++ 3.2): Develop skills in C and C++ programming, which are widely used in software development, game development, and system programming.

Java (JDK 11): Gain expertise in Java programming for application development, web development (Java EE), and Android app development.

Python (3.10): Learn Python programming for various applications, including web development, data analysis, machine learning, and automation.

R (4.2) and R Studio: Explore statistical computing, data analysis, and visualization using R.

SQL (Oracle Server/Client 11g, MySQL 8.0, SQL PLUS): Practice database management and SQL queries using different database systems.

Microsoft Visual Studio 2022 (17.1.6) and Apache NetBeans (12.5): Develop applications using integrated development environments (IDEs) for C++, Java, and other languages.

Anaconda Navigator, Jupyter (Anaconda 3 – 64 bit): Work on data science projects and explore machine learning using Python with Jupyter notebooks.

MATLAB (R2021 9.10): Learn and practice numerical computing, data analysis, and visualization.

Notepad++: Use a versatile text editor for coding and scripting in various languages.

Tableau (23.2): Gain skills in data visualization and analytics.

Wireshark (3.6): Learn about network protocols and packet analysis for network troubleshooting and security.

yEd Graphics Editor: Create and edit diagrams and flowcharts for various purposes.

VM Workstation and Ubuntu Virtual Box: Explore virtualization, run virtual machines, and practice working with different operating systems.

MobaXterm: Use as a terminal for remote system administration and network tools.

Click Here

This Laboratory supports the creation of resilient applications using R, Python, C, C++ and Java.Students have access to Microsoft Visual Studio-an Integrated Development Environment
(IDE) tool for creating web-based and mobile applications. Students can gain proficiency in data analysis and visualization through MATLAB, and can explore server virtualization using
VMware. Students may utilize NetBeans which supports J2EE and J2ME for server-side development and JavaScript, PHP, and C/C++ for cross-platform development.

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Students have access to a wide range of tools in the Programming Language – VI lab, including programming languages, software development processes, and methods for data analysis. Students can prepare for a range of occupations in computer science and related subjects by putting their theoretical knowledge to use in real-world circumstances and earning practical experience.

Students are provided with access to a wide range of tools and software, enabling them to study and practice many aspects of computer science, programming, and related fields..

What a student could do with the installed software to create creative software is described below:

• Operating systems: Linux Mint and Windows 11 Home (64-bit) for the development and execution of operating systems processes.
• C++ (Dev. C++, Turbo C++ 3.2): Develop skills in C and C++ programming, which are widely used in software development, game development, and system programming.
• Java (JDK 11): Gain expertise in Java programming for application development, web development (Java EE), and Android app development.
• Python (3.10): Learn Python programming for various applications, including web development, data analysis, machine learning, and automation.
• R (4.2) and R Studio: Explore statistical computing, data analysis, and visualization using R.
• Microsoft Visual Studio 2022 (17.1.6) and Apache NetBeans (12.5): Develop applications using integrated development environments (IDEs) for C++, Java, and other languages.
• Anaconda Navigator, Jupyter (Anaconda 3 – 64 bit): Work on data science projects and explore machine learning using Python with Jupyter notebooks.
• MATLAB (R2021 9.10): Learn and practice numerical computing, data analysis, and visualization.
• Notepad++: Use a versatile text editor for coding and scripting in various languages.
• Tableau (23.2): Gain skills in data visualization and analytics.
• Wireshark (3.6): Learn about network protocols and packet analysis for network troubleshooting and security.
• yEd Graphics Editor: Create and edit diagrams and flowcharts for various purposes.
• VM Workstation and Virtual Box: Explore virtualization, run virtual machines, and practice working with different operating systems.
• Microsoft office 2010 and Office 365 tools for documentation purpose

AB3 – 402 Lab

The Programming Language – VII laboratory has provided students with a wide range of tools for researching, among other things, data analysis techniques, software development approaches, and programming languages. By applying theoretical knowledge to real-world circumstances and acquiring practical experience, students can prepare for a wide range of careers in computer science and other subjects.

A student is given access to a large and diverse set of tools and software, allowing them to study and practice many aspects of computer science, programming, and related fields.

The following outlines what a learner can accomplish and create creative software utilizing the installed software.:

1. Operating systems: Windows 11 home (64-bit) and Ubuntu for Operating systems process creation and execution.
2. C++ (Dev. C++, Turbo C++ 3.2): Develop skills in C and C++ programming, which are widely used in software development, game development, and system programming.
3. Java (JDK 11): Gain expertise in Java programming for application development, web development (Java EE), and Android app development.
4. Python (3.10): Learn Python programming for various applications, including web development, data analysis, machine learning, and automation.
5. R (4.2) and R Studio: Explore statistical computing, data analysis, and visualization using R.
6. Microsoft Visual Studio 2022 (17.1.6) and Apache NetBeans (12.5): Develop applications using integrated development environments (IDEs) for C++, Java, and other languages.
7. Anaconda Navigator, Jupiter (Anaconda 3 – 64 bit): Work on data science projects and explore machine learning using Python with Jupiter notebooks.
8. MATLAB (R2021 9.10): Learn and practice numerical computing, data analysis, and visualization.
9. Notepad++: Use a versatile text editor for coding and scripting in various languages.
10. Wireshark (3.6): Learn about network protocols and packet analysis for network troubleshooting and security.
11. yEd Graphics Editor: Create and edit diagrams and flowcharts for various purposes.
12. VM Workstation and Virtual Box: Explore virtualization, run virtual machines, and practice working with different operating systems.
13. Microsoft office 2010 and Office 365 tools for documentation purpose.

AB3 – 412 Lab

The Programming Language – VIII Laboratory provides students with a comprehensive set of tools to explore data analysis techniques, software development methodologies, and programming languages. By applying theoretical concepts to real-world scenarios and gaining hands-on experience, students are better prepared for diverse careers in computer science and related fields.

Students have access to a diverse and extensive range of software, enabling them to study and practice various aspects of programming, software development, and computing. The following is an outline of the installed software and its applications:

1. Operating System:
   • Windows 11 Pro for process creation and execution.
2. Microsoft Office:
   • Microsoft Office Professional Plus for documentation purposes.
3. Programming Languages and Development Tools:
   • C++ Development: Dev C++ for software development and system programming.
   • Java Development: Java JDK, Apache NetBeans, and Eclipse-inst-jre for Java application and web development.
   • Python Development: Python for web development, automation, machine learning, and data analysis.
   • Node.js: A JavaScript runtime environment for backend development.
4. Statistical Computing and Data Analysis:
   • R and RStudio for statistical computing, data visualization, and data analysis.
5. Mathematical and Scientific Computing:
   • MATLAB for numerical computing, data analysis, and algorithm development.
6. Database Management:
   • Oracle (SQL Command Line) for database management and SQL query execution.
7. Web Development and Server Management:
   • XAMPP for local web server development.
8. Networking and Security:
   • Wireshark for network protocol analysis and security monitoring.
9. Project Management and Diagramming:
   • ProjectLibre for project scheduling and management.
   • StarUML for UML diagram creation and software modeling.
10. Virtualization Tools:
    • VirtualBox and VMware Player for running virtual machines and exploring different operating systems.
11. Development Environments and Editors:
    • Microsoft Visual Studio for software development across multiple languages.
    • Anaconda Navigator and Jupyter (Anaconda) for data science, machine learning, and scientific computing.
12. Web Browsers:
    • Google Chrome and Mozilla Firefox for web development, testing, and browsing.
13. NLP Tools:
    • NLTK (Natural Language Toolkit): For natural language processing tasks such as tokenization, stemming, and text analysis.
    • SpaCy: A library for advanced NLP tasks such as named entity recognition, dependency parsing, and text classification.
    • Hugging Face Transformers: A toolset for building, training, and deploying state-of-the-art NLP models like BERT and GPT.
    • FastText: For word embeddings and text classification.
    • Gensim: For topic modeling, document similarity analysis, and word embeddings. 

This laboratory provides students with an environment conducive to learning and innovation, equipping them with the necessary tools to develop creative software solutions and gain valuable technical expertise.

AB3 611 Lab

The Programming Language – IX laboratory has provided students with a wide range of tools for research like, data analysis techniques, software development approaches, and programming languages. By applying theoretical knowledge to real-world circumstances and by acquiring practical experience, students can prepare for a wide range of careers in computer science and other subjects.

A student is given access to a large and diverse set of tools and software, allowing them to study and practice many aspects of computer science, programming, and related fields. The development of robust applications with R, Python, C, C++, and Java is supported in this lab. Microsoft Visual Studio, an Integrated Development Environment (IDE) tool for making mobile and web applications, is available to students. With MATLAB, students can become proficient in data analysis and visualization, and with VMware, they can investigate server virtualization. Students can use NetBeans, which supports JavaScript, PHP, and C/C++ for cross-platform development, as well as J2EE and J2ME for server-side development. In academic and research contexts, Wireshark is frequently used to investigate network protocols, examine network activity, and carry out network-oriented research experiments.

How a student can use the installed applications to efficiently design and produce creative software is described as follows.

• Microsoft Office Professional Plus: Use for documentation purpose.
• MATLAB: Learn and practice numerical computing, data analysis, and visualization.
• R and RSTUDIO: Explore statistical computing, data analysis, and visualization using R.
• Chrome and Firefox: Use to access websites.
• Anaconda Navigation, Jupyter: Work on data science projects and explore machine learning using Python with Jupiter notebooks.
• Oracle: Provide the connectivity required to enable seamless interaction with Oracle Database servers.
• Java Jdk: Gain expertise in Java programming for application development, web development (Java EE), and Android app development.
• Apache-Net beans: Provide editors, wizards, and templates to create applications in Java, PHP and many other languages.
• Eclipse-inst-jre: Run and debug java programs.
• C++: Develop skills in C and C++ programming, which are widely used in software development, game development, and system programming.
• Node js: Create real-time applications, web apps, and back-end applications.
• ProjectLibre: Create, manage, and track project plans by utilizing features like Gantt charts, task dependencies, resource allocation, and progress tracking.
• Python: Learn Python programming for various applications, including web development, data analysis, machine learning, and automation.
• StarUML: Create flowcharts and UML diagrams, to help with software development.
• VMware-Player and VirtualBox: Explore virtualization, run virtual machines, and practice working with different operating systems.
• Wireshark: Learn about network protocols and packet analysis for network troubleshooting and security.
• Xampp: Allow developers to test their code locally.
• Visual Studio: Develop applications using integrated development environments (IDEs) for C++ and other languages.

About the lab:
Robotics lab at VIT Chennai has been established for the students to gain the knowledge and to get exposure on simulations along with understanding the functioning of robots. Students will be made competent in understanding the basic functions of few general purpose robots and they will be allowed to implement their skills on DOBOT Magician Educational Kit and NAO humanoid robot. Sufficient numbers of LEGO EV3 Core sets are available for the students to understand the various hardware components, simulations and for the implementation. The following are the few set of experiments included in practical classes.

AIR Lab contains the following equipment in sufficient number to conduct the following experiments.
LEGO EV3 Core Set

• Obstacle sensing
• Edge finding
• Path following
• Solving Rubik’s Cube
• Cloth folding
• Chess Robot
• Musical instruments playing

DOBOT Magician is a multifunctional desktop robotic arm for practical training education

• Laser engraving
• Writing and drawing
• Scrap classifying
• Vegetable / fruit picking
• Package sorting
• AI assisted smart shopping system

NAO  – The Humanoid and Programmable Robot

Nao is a small humanoid robot designed to interact with people. It’s packed with sensors (and character) and it can walk, dance, speak, and recognize faces and objects. Now in its sixth generation, it is used in research, education, and healthcare all over the world.

Nao is an autonomous, programmable, medium-sized humanoid robot in which the architecture of control and the software are customizable. NAO was designed to walk smoothly, even when changing speed and direction. The robot has the capability of performing a rich panel of movements with smoothness and precision, and a certain degree of interactive autonomy. NAO is modular, referring to actuator modules that can be used for different joints. The head of NAO changed.

In universities or schools using NAO, students and teachers are developing projects such as: how to mimic a student’s body posture, navigate through a room or recognise objects.

In computer science, use NAO platform to discover algorithmic logics basics or teach object oriented, embedded or real time programming.  In control, use ankle to define the control law of a 2 DOF system or use NAO platform to define complex control mixing vision/motion/audio.

Scientific research is being conducted in the following areas with NAO platform: robotics, mapping, object recognition, grasping, walking, motion, autism, human machine interaction / ethics, navigation in complex indoor environments, object category recognition & detection.

At beginner level, you can redesign basic mechanical parts using NAO CAD files as well as work on torque computation or sensors study. At advanced level, students can use their math skills to perform matrix computation to work on NAO kinematics.

* Images / text is taken from relevant sources.

Hardware and Software details

The objective of the Software Engineering Laboratory is to familiarize students with the Software Development Life Cycle (SDLC) so that they are trained well in the various phases of SDLC, testing tools. Students are trained with software packages. The Laboratory has about 68 Pentium D systems. Students do various projects related to software metrics, software testing, quality assurance, software project management and software design.

AB209 Lab

Name of the Laboratory: AB3 -311 SMARTS (Strategic Machine Automation and Robotic Technology Solutions) laboratory

School: School of Computer Science and Engineering (SCOPE)

About the Laboratory:

SMARTS lab of VIT Chennai caters the need of students learning requirement in the field of robotics with diversified versions of robot. This lab consists of different types of   mobile robotic kit that includes educational version of mobile robots and industrial standard mobile robotic platforms.SMARTS lab consists of discrete components including sensors, actuators, microcontrollers and embedded boards that helps students to assemble a robotic system according to the need and requirement for their assignments, lab experiments and capstone projects. These lab activities helps students to learn the practical experimentation and hands on experience about mobile robots. These mobile robots are programmable along with hardware interface facility which makes students to excel in the different field of study like programming skills and hardware interface. Students are also given exposure towards open source robot programming packages like Robot Operating Systems (ROS).This SMARTS lab supports UG, PG students and research scholars for multidisciplinary learning in the field of robotics.

Major facilities available in SMARTS lab:

Major facilities and hardware components available in SMARTS laboratory used for carrying out the following experiments in the autonomous systems and mobile robots are

1. Path planning
2. Obstacle avoidance
3. Velocity control
4. Motion control
5. Map building
6. Testing of autonomous mobility
7. SLAM concepts
8. Mobility of robots in multi terrain surface
9. Digital Twin of industrial mobile robots
10. Tele operation of mobile robots

Major Equipment

Possible collaborations with industries for consultancy and research activities at SMARTS Laboratory

• Experimental research in the area of mobile robots
• Path planning, motion control, velocity control, and obstacle avoidance algorithms can be developed
• ROS, Gazebo-based software tools, can be used for working in a simulation environment
• The newly developed working environment in the simulation platform can be physically tested using the available lab equipment