Kaustubh Nigam

References Read

  1. "Using machine learning to understand customer behaviour" shared by Wong Ngo Yin

Rating 90/100 The article provides a good mathematical and computational approach. What I would love to know is the estimated decreased cost.

2. "Do motion Sensor light switches worth it?" shared by Suntoso Sean Michael

Rating 85/100 The method provides a good approach for smaller scale. The data is equally appropriate as it provides a good estimate on the savings. I would love to hear about the larger scale as well in the future.

3. "Saving Energy consumption with deep learning" shared by Kwan Rafael Matthew Susanto

Rating 85/100 How much time until the cost of this solution is brought down? Is this better than what Deep Mind is doing? I really like their work in the field though.

4."Forecasting Solar Energy production using Artificial Intelligence" shared by Kwan Rafael Matthew Susanto

Rating 80/100 Deep Mind is doing something similar with Wind Energy. Might want to take a look.

5. "HK Case: Samsung Energy Management" shared by Guillemot Raphaele Michelle

Rating 70/100 How much acceptance has this gained among the people in these 7 years? Is it affordable enough initially for the average consumer?

6."Homemade bicycle generator//Burn Calories and Make Electricity" shared by Kwan Rafael Matthew Susanto

Rating 90/100 There are villages in India that use this technology to shear sheep. Good for areas with bad supply of electricity.

7. "The future of Energy Storage beyond Lithium Ion" shared by Suntoso Sean Michael

Rating 90/100 Samsung is looking into Graphene batteries as well for mobile phones which might be 1/3 rd of the cost of lithium ion batteries.

8."Estimated running cost of electrical appliances" shared by Ngo Yin Wong

Rating 80/100 The data can be used for analysis when integrating AI. However, heavy usage consumers cost would vary.

9. "How AI lighting can fool you into thinking lights are on" shared by Suntoso Sean Michael

Rating 95/100 The algorithm can be very useful especially with the percentage savings it is offering.

10. "Global energy and CO2 emissions in 2019" shared by Ngo Yin Wong

Rating 95/100 The provided data can be used to understand a population's behaviour towards energy resources in case of natural calamities such as the pandemic.