Blockchain
When we reflect on the future of agriculture, we could not avoid thinking about the power of technology to solve problems bedeviling this sector. Climate change, population growth and food security concerns have pushed for innovative technological solutions to farming.
Artificial Intelligence is emerging as part of the solutions towards improved agricultural productivity.Individual agricultural activities on the farm takes effort, for example planting, maintaining, and harvesting crops need money, energy, labor and resources. What if we can use technology to replace some of the human activities and guarantee efficiency? That’s where artificial intelligence comes in.
Vishakh Dadwal
- Exceptional presentation skills.
- Strong leadership and problem thinking skills.
- Exceptional Communication skills in written and verbal both.
- Able to give the best result in pressure situations.
Yashvi
- Excellent academic score.
- Exceptional presentation skills.
- Strong leadership and problem thinking skills.
- Exceptional Communication skills in written and verbal both.
- Able to give the best result in pressure situations.
- Excellent in presenting and make people understand.
- A detail oriented and multitasking professional pursuing bachelor of engineering degree in computer engineering.
Valentinus Mitchell Rahina Surya
- Self Motivate and a good team player.
- Quick and always eager to learn new technologies.
- Good analysis-synthesis and reasoning skills.
- Great Communication Skills.
- Able to Multitask, work in group and work under pressure.
Landslide
In this research we have used item-based collaborative filtering to obtain the relationship between various incident sensed by the sensors in consequent time points. The information obtained from consequent time points is used to predict the data values for next time points. Multi-source and temporal correlations are used to reduce data transmission.
Hansa
- Good Managerial and interpersonal skills.
- Self motivated, focused and dedicated.
- Good Communication Skills
- In possession of a pleasant personality complemented with a caring and responsible attitude.
Onkar
- Programming languages: Python ,C & Java.
- DBMS: Oracle 9i (basic).
- Web Development: PHP, HTML, CSS, JavaScript & Bootstrap.
- Framework: Django.
- Tools: Netbeans, Pycharm, Vmware, Virtualbox, Eclipse, Git.
- Networking Qualification: CCNA.
Smart Farming
In our research we have tried to develop a deep learning framework for crop growth prediction
which predicts the stage of the crop growth and crop pathology prediction which predicts
whether the plant is healthy or unhealthy and if unhealthy in which of unhealthy stage it is. For
crop growth prediction we have used the synthetic dataset generated from DSSAT simulator to
train our deep learning framework model. Basically it consists of two components namely
atmospheric module and soil module. In model we have used total 24 features to predict the
different stages of crop growth (Table.1).For crop pathology we have used two different datasets
and proposed two models for the respective datasets.
Nathanael Ardisa
- C#
- Assembly
- Basic MATLAB
Harshdeep Kaur
-
Six Months Industrial training: Jan-May 2017
From Impinge Solutions, Phase-8, Mohali, Chandigarh -
Project title: ‘Online Parking System (Quick Parking).’
Technologies used: Front End: Android Studio; Back End: Oracle -
Six Weeks Industrial training: From Techhive, Amritsar, Punjab
The training was undertaken in Core Java programming language. -
Project title: ‘Suspicious Mail Detection.’
Technologies used: Front End: Core Java; Back End: File Handling -
Six Weeks Industrial training: From Soneil Tech Solutions, Gurdaspur, Punjab
The training was undertaken in PHP. -
Project title: ‘Student Record System’
Technologies used: Front End: PHP; Back End: MySQL -
Six Weeks Industrial training: From NIIT, Dinanagar, Punjab
The training was undertaken in PHP. -
Project title: ‘Musical Website’
Technologies used: Front End: PHP; Back End: File Handling
Smart Traffic
In this internship project, I have implemented various end to end learning techniques to drive
an autonomous vehicle on Udacity’s Simulator. I used a Convolutional Nueral Network to
directly map raw set of image pixels to steering angle of car in case of Supervised Learning
, while in case of End to End DQN I have mapped the image pixels to the Q values
associated with each action. The supervised learning is able to drive the car around the
car as demonstrated in the video file attached with this project. Supervised Learning is
showing good results as compared to a DQN but that might be because a DQN requires a
lot more learning than Supervised Learning and moreover a DQN needs to learn a lot more
values as compared to a supervised learning model. It seems as if both of these models are
trying to estimate where the middle of road is and are taking actions to reach the middle
of the lane. This is because middle of the lane is the safest position for any model.
Jehoshua Hanky Pratama
- Well organized and creative in problem solving
- Hard worker, have ability to learn and easily adopt to recent technologies
- Great Communication skills
Michael Griffith
- Able to understand and solve problems with complex difficulty quickly
- Stand out in concept of arithmethic, mechanical principles and spatial principles
- Good analysis-synthesis and reasoning skills
- Able to analyze problems from various viewpoints, draw a conclusion sharply, and able to analyze problems clearly and logically
Durgendra Pratap Singh
- Computing and Algorithms : C, C++,Java, R, OWL, JavaScript, MATLAB ,Python, SQL and sqlite, SPARQL, UML, Verilog HDL, XML
- Hardware Prototyping : Arduino, Raspberry Pi.
- Professional Software : Cadence Virtuoso, Multisim, Xilinx, Eclipse, NetBeans, gcc, g++, Android Studio
- Operating System : Linux, Windows
Narotam Singh
- Languages: C, C++, Python
- Tools: Visual Studio, MATLAB, OpenCV, Keras, LIBSVM, LaTeX
- Operating Systems: Windows, Linux
Sachin Bijalwan
- C, C++, java, PHP, Python
- Android Studio
- Machine learning
- Artificial Intelligence
Parikshit Kumar Pruthi
- Programming Language : Java, C, C++, MATLAB, HTML, CSS, Javascript, JQuery, Python
- Tools and Technologies : Arduino, FPGA, Raspberry Pi, AVR, Tinker CAD, Blender, Photoshop, LT Spice, Eagle, Verilog, Android(Beginner)