Back close

Study of Socio-Economic Aspects of Sustainability and Influence of Human Behavior in Efficient Energy Usage Using Machine Learning

Dept/Center/Lab: Amrita Center for Wireless Networks and Applications (AWNA)

Project Incharge:Reshma Reghunadh
Co-Project Incharge:Dr. Aryadevi R. D.
Study of Socio-Economic Aspects of Sustainability and Influence of Human Behavior in Efficient Energy Usage Using Machine Learning

Energy sustainability is a critical global concern, and understanding the intricate relationship between social factors and human behavior in the context of efficient energy usage is essential for devising effective energy conservation strategies. Machine learning techniques provide an innovative approach to gain insights from vast datasets and develop predictive models that can guide policy and behavior change interventions. The outcomes of this research will contribute valuable insights and recommendations to promote efficient energy usage and support sustainability efforts. This research will guide policy decisions and foster positive changes in individual and community behavior towards sustainable energy practices.

Name of staff and students from Amrita

  • Dr. Maneesha V Ramesh, Director and Professor, Amrita Center for Wireless Network & Application,
  • Dr. Muralee Krishnan C, Associate Professor, Amrita School of Business, Coimbatore
  • Dr. Rahul Krishnan, Assistant Professor, Amrita Center for Wireless Network & Application
  • Dr. M R Kaimal – Professor, School of Computing, Amritapuri

Name of the International Collaborators : Dr. Emitza Guzman Ortega, Assistant Professor, Faculty of Science, Software and Sustainability (S2), Assistant Professor, Network Institute Assistant Professor, Information Management & Software Engineering

Related Projects

Decoding of Turbo Product Codes using Deep Learning Technique
Decoding of Turbo Product Codes using Deep Learning Technique
Identification of Endophytes from Marine Algae by 16S rRNA sequencing
Identification of Endophytes from Marine Algae by 16S rRNA sequencing
Mobile Ocean Sense: Utilizing Fishing Vessels for Ocean Data Collection
Mobile Ocean Sense: Utilizing Fishing Vessels for Ocean Data Collection
An exploratory clinical study to determine the utility of heart rate variability analysis in the assessment of doṣa imbalance
An exploratory clinical study to determine the utility of heart rate variability analysis in the assessment of doṣa imbalance
Synthesis and Preliminary Evaluation of Ring
Synthesis and Preliminary Evaluation of Ring
Admissions Apply Now