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Advance Stochastic Point Process Techniques: Modeling Problems in the Internet of Things (IoT) and Marketing

Data Science and Analytics

ISBN: 978-1-80043-877-4, eISBN: 978-1-80043-876-7

Publication date: 4 December 2020

Abstract

This chapter has been seminal work of Dr K.S.S. Iyer, which has taken time to develop, for over the last 56 years to be presented here. The method in advance predictive analytics has developed, from his several other applications, in predictive modeling by using the stochastic point process technique. In the chapter on advance predictive analytics, Dr Iyer is collecting his approaches and generalizing it in this chapter. In this chapter, two of the techniques of stochastic point process known as Product Density and Random point process used in modelling problems in High energy particles and cancer, are redefined to suit problems currently in demand in IoT and customer equity in marketing (Iyer, Patil, & Chetlapalli, 2014b). This formulation arises from these techniques being used in different fields like energy requirement in Internet of Things (IoT) devices, growth of cancer cells, cosmic rays’ study, to customer equity and many more approaches.

Keywords

Citation

Iyer, K.S.S. and Damle, M. (2020), "Advance Stochastic Point Process Techniques: Modeling Problems in the Internet of Things (IoT) and Marketing", Kumari, S., Tripathy, K.K. and Kumbhar, V. (Ed.) Data Science and Analytics, Emerald Publishing Limited, Bingley, pp. 91-102. https://doi.org/10.1108/978-1-80043-876-720211006

Publisher

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Emerald Publishing Limited

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