It may be possible for MIT like institute to develop the control alogorithms based upon adaptive learning methods.
For example , based upon the currently available knowledge and the real time 3D data available from the sensors , the autonomous system can still remain in the learning mode while allowing the driver to have full control of the car. The system can then note down the driver actions vs. the analysis done by the system as per the sensor data and can prepare a kind of rule table. Over a period this rule table gets refined and refined so much that the system can use that rule-based table to make autonomous driving decisions.
What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Are the design challenges the same as with embedded systems, but with a little developer- and IT-skills added in? What do engineers need to know? Rick Merritt talks with two experts about the tools and best options for designing IoT devices in 2016. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.