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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.

The major component of agriculture production includes the type of seed, soil, climatic conditions, irrigation pattern, fertilizer, weed control, and technology used. Soil is one of the prime elements in modern times for agriculture. Soil is also one of the primary and important factors for crop production. The available soil nutrient status and external applications of fertilizers decide the growth of crop productivity (Annoymous, 2017). The upcoming research question that needs to be addressed is What is the application of soil data on soil health management for sustaining agriculture? Driven by the need, the aim of the present study is (a) to explore the soil parameters of a district, (b) compare the values with the standards, and (c) pave a way for mapping the crops with suitability of soil health. This study will not only be beneficial for the district to take appropriate steps to improve the soil health but also would help in understanding the causal relationship among soil health parameters, cropping pattern, and crop productivity.

A major chunk of rural people live on agriculture and other allied activities viz animal husbandry, dairying and fisheries, etc. Rural development constitutes of lot of big data related to rural employment which has driven this study to address a research question that what is the application of big data in rural development with special reference to the world’s largest public works and wage employment generating poverty alleviation program – Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA)? The concepts of MGNREGA are novel and innovative though the program continues to suffer from various rigidities depicted from the data. This drives us to the objectives of our research. The objective of the study is to explore literature and big data on rural development with special reference to MGNREGA, explore the upcoming challenges in rural employment with special reference to MGNREGA, identify gaps in existing literature and pave out future research direction. The present study paves various ways for future research directions for academicians, researchers and policy maker.

Predictive analytics is the science of decision-making that eliminates guesswork out of the decision-making process and applies proven scientific procedures to find right solutions. Predictive analytics provides ideas on the occurrences of future downtimes and rejections thereby aids in taking preventive actions before abnormalities occur. Considering these advantages, predictive analytics is adopted in various diverse fields such as health care, finance, education, marketing, automotive, etc. Predictive analytics tools can be used to predict various behaviors and patterns, thereby saving the time and money of its users. Many open-source predictive analysis tools namely R, scikit-learn, Konstanz Information Miner (KNIME), Orange, RapidMiner, Waikato Environment for Knowledge Analysis (WEKA), etc. are freely available for the users. This chapter aims to reveal the best accurate tools and techniques for the classification task that aid in decision-making. Our experimental results show that no specific tool provides the best results in all scenarios; rather it depends upon the datasets and the classifier.

Aadhaar card is an innovative step taken by the Government of India to facilitate smooth functioning of government welfare programs among the needy citizens of this country. This chapter deals about the Aadhaar Project of the Central Government, its features, its impact on the welfare schemes of government, etc. Second, it also deals with the challenges and loopholes associated with the Aadhaar scheme which eventually led to the case of Justice K. S. Puttaswamy and Another v. Union of India [Writ Petition (Civil) No. 494 of 2012]. At last, the chapter deals with the potential challenges which the Aadhaar scheme may face even after it has been declared constitutional by the Apex Court in the case of Justice K. S. Puttaswamy and Another v. Union of India [Writ Petition (Civil) No. 494 of 2012].