Ideas From KCG Innovation Challenge

We started with 40 ideas ( 5 each from 8 departments). After initial screening, we selected 16 ( 2 from each department) and had them present to an external jury. Here are a list of these ideas. we will award three top ideas. We will support many of these ideas turn to prototypes.

  1. Robotic sewage Cleaners
  2. Detecting Landmines Using QuadCopter
  3. Partial Replacement of Natural Course Aggregate with Plastic Aggregate
  4. BIM Modelling using alternate Realities
  5. Voice ATM
  6. IOT based fire alert system
  7. Detecting and helping Dyslexia in Children
  8. Detecting early signs of foot problems for Diabetic Patients
  9. Automating powering up and down classrooms in a college
  10. Water Management system using IOT
  11. Automatic segregation of  recyclable material
  12. Hybrid Solar Panel
  13. MTC Bus Tracking
  14. IOT based Smart glasses
  15. Flexible and Compact couch
  16. Temperature control Jacket

What is Build to Learn?

Build to Learn is an initiative by a group of volunteers to help people learn programming by building useful micro-products. Our motto is – Build to Learn and Learn to Build.

Anyone who wants to learn or build or do both can participate. We plan to meet a few times a week in 3-4 hour coding sessions and build useful products.

The setting is informal. You can start with a simple one paragraph definition of a product and recruit volunteers to work with you on the idea. We do not have any rigid processes. The team can decide how to interact.

We had the first session on the 3rd of February and 10 of us were present. We started 4 projects. We hope you can all join and either learn or help others learn.

Who can participate? Anyone who wants to help  define  a product, code, design, and  test.

 

Technology in Farming – Robots, Mixed Reality, Machine Learning

Is manual farming sustainable as the need for agricultural products grow in demand? Can technology help? How does it impact lives of farmers? Is it the right thing to do? Like any other applications of technology, there are more questions than answers. The following links are just a set of leading indicators of trends.

Agricultural vehicles known as “cucumber flyers” enable as many as 50 seasonal workers to harvest crops.
Experts from Fraunhofer IPK in Berlin, along with other German and Spanish researchers, are studying the potential for automating cucumber harvests in the scope of the EU project CATCH, which stands for “Cucumber Gathering – Green Field Experiments.” Project partners are the Leibniz Institute for Agricultural Engineering and Bioeconomy in Germany and the CSIC-UPM Centre for Automation and Robotics (CAR) in Spain.
During the Hands Free Hectare project, no human set foot on the field between planting and harvest—everything was done by robots. This includes:
  • Drilling channels in the dirt for barley seeds to be planted at specific depths and intervals with an autonomous tractor;
  • Spraying a series of fungicides, herbicides, and fertilizers when and where necessary;
  • Harvesting the barley with an autonomous combine.

How mixed reality and machine learning are driving innovation in farming

The Economist, in its Q2 Technology Quarterly issue, proclaims agriculture will soon need to become more manufacturing-like in order to feed the world’s growing population. Scientific American reports crops will soon need to become more drought resistant in order to effectively grow in uncertain climates. Farms, The New York Times writes, will soon need to learn how to harvest more with less water.