I have Wireless Sensor Network setup in a classroom. I'm sensing data like temp, humidity, light, occupancy, etc. Classroom can accommodate 150 students and has 6 AC with light. From one side the classroom has big windows and that side is towards west and other 3 sides have thick walls and doors always closed. I have been looking for some questions that can be answered by analyzing data collected. Some of the questions I can think of are:

  • Predicting optimum time to turn on AC before class starts so that class is attains required temp with least energy consumed.
  • As of now I have 9 sensors on all walls and ceiling too. So to decide best position for sensor such that I can co-relate and predict other sensor values from only one or two sensor values.
  • Decide optimum amount of light needed by occupants to be comfortable in classroom.

Please suggest to me more questions that can asked about this situation. Also suggest if I can use somehow machine learning in WSN I have deployed.


1 Answer 1


Very difficult question for someone to answer as ultimately your examples and many questions contain certain constraints you won't get from your sensors. For example: Your first question is predicting "optimum" time to turn on AC. who defines optimum? Optimum for the classroom at full capcity, half capacity? Your second question looks like it one, requires a map of the classroom and where the sensors are, two you won't be able to predict 7 sensor values from 2 sensor values, I don't know why you would want to do this. Your third questions is a social sciences problem. Define "light needed to be comfortable". I imagine you would get 150 answers if you had 150 students.

Your scenario lacks context/comparison. Let's say you had sensors outside the classroom for your various data points. Then you could do things like, can I predict the temp inside the room based on my other room and external data points.

Finally, yes machine learning can be used with your wireless sensors.


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