With the advancement of technology and growing business needs it is vital that the services offered to customers across various applications need to be proactive and not reactive. This work extends the existing cloud framework available for smart homes that offers extended potential business opportunities to service providers and optimistic smart services to end users. Based on the defined framework cluster analysis is done to derive the customer segmentation that facilitates smart home service providers to offer efficient services and to improve the product upselling. The predicted energy consumption is derived using linear regression, for the end users to be energy efficient. Here a deeper analysis based on the data generated from devices and smart home applications is carried out to offer proactive consumer services and to have economical energy consumption.

Smart Serivces, Machine Learning, Smart Homes, Internet of Things

[1] Towards Datascience. https://towardsdatascience.com/15-artificial-intelligence-ai-stats-you-need-to-know-in-2018-b6c5eac958e5
[2] Dataversity. http://www.dataversity.net/machine-learning-algorithms-today-usage-results/
[3] Forbes. https://www.forbes.com/sites/freddiedawson/2015/09/30/smart-home-sector-could-be-worth-hundreds-of-billions-in-next-five-years/#310e8bbe6a20
[4] Tyagi, Sapna, Ashraf Darwish, and Mohammad Y. Khan. "Managing computing infrastructure for IoT data." (2014).
[5] Botta, Alessio, et al. "On the integration of cloud computing and internet of things." Future internet of things and cloud (FiCloud), 2014 international conference on. IEEE, 2014.
[6] Stojkoska, Biljana L. Risteska, and Kire V. Trivodaliev. "A review of Internet of Things for smart home: Challenges and solutions." Journal of Cleaner Production 140 (2017): 1454-1464.
[7] C. Premalatha, "Automatic Smart Irrigation System Using IOT", International Journal of Scientific Research in Computer Science and Engineering, Vol.7, Issue.1, pp.1-5, 2019
[8] Koduru, Suresh, VGD Prasad Reddy Padala, and Preethi Padala. "Smart Irrigation System Using Cloud and Internet of Things." Proceedings of 2nd International Conference on Communication, Computing and Networking. Springer, Singapore, 2019.
[9] Vidhi Tiwari, Pratibha Adkar, "Implementation of IoT in Home Automation using android application", International Journal of Scientific Research in Computer Science and Engineering, Vol.7, Issue.2, pp.11-16, 2019
[10] Zaouali, K., et al. "Incoming data prediction in smart home environment with HMM-based machine learning." Signal, Image, Video and Communications (ISIVC), International Symposium on. IEEE, 2016.
[11] Chung, Che-Min, et al. "Automated machine learning for Internet of Things." Consumer Electronics-Taiwan (ICCE-TW), 2017 IEEE International Conference on. IEEE, 2017.
[12] Suresh, K., Prasad Reddy, PVGD., Preethi, P. (2019). Smart Home Services using Cloud and Internet of Things. Manuscript submitted for publication.
[13] SAP Fiori – SAP UI5, https://archive.sap.com/documents/docs/DOC-46225
[14] SAP UI5,
https://sapui5.hana.ondemand.com/#docs/guide/95d113be50ae40d5b0b562b84d715227.html
[15] Python. https://www.python.org/
[16] Eastern Power Distribution Company of AP Ltd.
https://www.apeasternpower.com/EPDCL_Home.portal;jsessionid=k23ybnwM1pFsk4GZBQcQTLZmJnypTJ5x1pnp8PhZz20ySkr4LfYn!161743796?_nfpb=true&_pageLabel=EPDCL_Home_portal_page_97