57
Internet of Things and Artificial Intelligence
promising area of research. We have proposed to use the smart grid as a step to connect
all power grids for efficient energy management. In future, several experiments are proposed to be conducted in smart traffic, smartphones, smart parking system, etc., in order
to obtain a viable solution for the several potential IoT applications of AI into tomorrow’s
digital world.
References
Aadhityan, A. 2015. A novel method for implementing artificial intelligence, cloud and Internet of Things
in robots. In IEEE Sponsored 2nd International Conference on Innovations in Information Embedded and
Communication Systems ICIIECS’15, March 19–20, Coimbatore, India.
Al-Ali, A. R. and Aburukba, R. 2015. Role of Internet of Things in the smart grid technology,
Journal of Computer and Communications, 3, 229–233.
Ashton, K. 2009. That ‘‘Internet of Things’’ thing, RFiD Journal, http://www.rfidjournal.com/articles/
pdf?4986 (accessed February 16, 2017).
Aung, Z., Toukhy, M., Williams, J. R., Sanchez, A., and Herrero, S. 2012. Towards accurate electricity
load forecasting in smart grids. In DBKDA 2012: The Fourth International Conference on Advances
in Databases, Knowledge, and Data Applications, IARIA, February 29–March 5, Sainet Gilles,
Reunion Island, pp. 51–57.
Bandyopadhyay, D. and Sen, J. 2011. Internet of things: Applications and challenges in technology
and standardization, Wireless Personal Communications, 58(1), 49–69.
Barker, S., Mishra, A., Irwin, D., Cecchet, E., Shenoy, P. and Albrecht, J. 2012. Smart*: An open data
set and tools for enabling research in sustainable homes. In Proceedings of the 2012 Workshop on
Data Mining Applications in Sustainability (SustKDD 2012), Beijing, China, August 2012, pp. 1–6.
Bhattacharyya, S. C. and Thanh, L. T. 2004. Short-term electric load forecasting using an artificial
neural network: Case of Northern Vietnam, International Journal of Energy Research, 28(5),
463–472.
Busseti, E., Osband, I. and Wong, S. 2012. Deep Learning for Time Series Modeling, Technical Report,
Stanford University, https://pdfs.semanticscholar.org/a241/a7e26d6baf2c068601813216d3cc09e845ff.pdf (accessed June 24, 2017).
Castellani, A. P., Bui, N., Casari, P., Rossi, M., Shelby, Z. and Zorzi, M. 2010. Architecture and protocols
for the Internet of Things: A case study. In IEEE International Conference on Pervasive Computing
and Communications Workshops (PERCOM Workshops), http://www.dei.unipd .it/~rossi/papers/
WOT_camera_2010.pdf
Connor, J., Martin, R. D. and Atlas, L. E. 1994. Recurring neural networks and robust time series
prediction, IEEE Transactions on Neural Networks, 5(2), 240–254.
Eijndhoven, D. 2016. The Internet of (Insecure) Things: Cyber Security Goofs in IoT Devices. http://www.
altran.nl/fileadmin/medias/NL.altran.nl/documents/Don_Eijndhoven_-_The_Internet_of_
Insecure_Things.pdf (accessed February 16, 2017).
EU_Commission. 2009. Internet of Things—An Action Plan for Europe. http://ec.europa.eu/information_
society/policy/rfid/library/index_en.html (accessed June 24, 2017).
Goodfellow, I., Bengio, Y. and Courville, A. 2016. Deep Learning, MIT Press, Cambridge, MA.
Hong, T. 2010. Short Term Electric Load Forecasting, https://repository.lib.ncsu.edu/bitstream/
handle/1840.16/6457/etd.pdf?sequence=2&isAllowed=y (accessed June 24, 2017).
Jain, P., Noor, A. and Sharma, V., 2011. Internet of Things an introduction. In Proceedings of ASCNT
C-DAC India, March 2, Noida, India, pp. 1–9.
Kavousian, A., Rajagopal, R. and Fischer, M. 2012. A Method to Analyze Large Data Sets of Residential
Electricity Consumption to Inform Data -Driven Energy Efficiency, CIFE Working Paper #WP130,
Stanford University, Stanford, CA.
Internet of Things and Artificial Intelligence
promising area of research. We have proposed to use the smart grid as a step to connect
all power grids for efficient energy management. In future, several experiments are proposed to be conducted in smart traffic, smartphones, smart parking system, etc., in order
to obtain a viable solution for the several potential IoT applications of AI into tomorrow’s
digital world.
References
Aadhityan, A. 2015. A novel method for implementing artificial intelligence, cloud and Internet of Things
in robots. In IEEE Sponsored 2nd International Conference on Innovations in Information Embedded and
Communication Systems ICIIECS’15, March 19–20, Coimbatore, India.
Al-Ali, A. R. and Aburukba, R. 2015. Role of Internet of Things in the smart grid technology,
Journal of Computer and Communications, 3, 229–233.
Ashton, K. 2009. That ‘‘Internet of Things’’ thing, RFiD Journal, http://www.rfidjournal.com/articles/
pdf?4986 (accessed February 16, 2017).
Aung, Z., Toukhy, M., Williams, J. R., Sanchez, A., and Herrero, S. 2012. Towards accurate electricity
load forecasting in smart grids. In DBKDA 2012: The Fourth International Conference on Advances
in Databases, Knowledge, and Data Applications, IARIA, February 29–March 5, Sainet Gilles,
Reunion Island, pp. 51–57.
Bandyopadhyay, D. and Sen, J. 2011. Internet of things: Applications and challenges in technology
and standardization, Wireless Personal Communications, 58(1), 49–69.
Barker, S., Mishra, A., Irwin, D., Cecchet, E., Shenoy, P. and Albrecht, J. 2012. Smart*: An open data
set and tools for enabling research in sustainable homes. In Proceedings of the 2012 Workshop on
Data Mining Applications in Sustainability (SustKDD 2012), Beijing, China, August 2012, pp. 1–6.
Bhattacharyya, S. C. and Thanh, L. T. 2004. Short-term electric load forecasting using an artificial
neural network: Case of Northern Vietnam, International Journal of Energy Research, 28(5),
463–472.
Busseti, E., Osband, I. and Wong, S. 2012. Deep Learning for Time Series Modeling, Technical Report,
Stanford University, https://pdfs.semanticscholar.org/a241/a7e26d6baf2c068601813216d3cc09e845ff.pdf (accessed June 24, 2017).
Castellani, A. P., Bui, N., Casari, P., Rossi, M., Shelby, Z. and Zorzi, M. 2010. Architecture and protocols
for the Internet of Things: A case study. In IEEE International Conference on Pervasive Computing
and Communications Workshops (PERCOM Workshops), http://www.dei.unipd .it/~rossi/papers/
WOT_camera_2010.pdf
Connor, J., Martin, R. D. and Atlas, L. E. 1994. Recurring neural networks and robust time series
prediction, IEEE Transactions on Neural Networks, 5(2), 240–254.
Eijndhoven, D. 2016. The Internet of (Insecure) Things: Cyber Security Goofs in IoT Devices. http://www.
altran.nl/fileadmin/medias/NL.altran.nl/documents/Don_Eijndhoven_-_The_Internet_of_
Insecure_Things.pdf (accessed February 16, 2017).
EU_Commission. 2009. Internet of Things—An Action Plan for Europe. http://ec.europa.eu/information_
society/policy/rfid/library/index_en.html (accessed June 24, 2017).
Goodfellow, I., Bengio, Y. and Courville, A. 2016. Deep Learning, MIT Press, Cambridge, MA.
Hong, T. 2010. Short Term Electric Load Forecasting, https://repository.lib.ncsu.edu/bitstream/
handle/1840.16/6457/etd.pdf?sequence=2&isAllowed=y (accessed June 24, 2017).
Jain, P., Noor, A. and Sharma, V., 2011. Internet of Things an introduction. In Proceedings of ASCNT
C-DAC India, March 2, Noida, India, pp. 1–9.
Kavousian, A., Rajagopal, R. and Fischer, M. 2012. A Method to Analyze Large Data Sets of Residential
Electricity Consumption to Inform Data -Driven Energy Efficiency, CIFE Working Paper #WP130,
Stanford University, Stanford, CA.