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Retirement is a psycho social process. It refers to the phase of life when a person leaves his job and withdraws from active working life. Proper optimization of retirement is only possible when a person has pre planned his life with proper finances and saving or the government is providing him with a lot of social security benefits. However, such conditions rarely occur as a person is preoccupied in his pre retirement phases. But proper optimization of retirement can also take place when a person has high social intelligence which affects physical and mental health. Hence, this paper is an endeavor to look into the relevance of social intelligence which helps the people in their retirement process in the people. Thus, a survey was done to find the level of Social Intelligence in the people who are ageing and are going to be retired soon. Around 252 people between 55 to 70 years were studied from Delhi and NCR. The result indicated that middle aged and just retired people had high social intelligence as compared to older adults and the former were also able to optimize their retirement effectively for successful ageing. The older adults were not able to cope up with the various issues of retirement due to low social intelligence. Hence, further studies can be carried out to design proper training for enhancement of social intelligence in aged people for their effective optimization of retirement.

The vehicular ad-hoc network (VANET) has emerged as the most sought-after technology due to its wide range of applications. In this modern era, people are looking for intelligent systems that include intelligent transport systems, which is not possible without the use of modern techniques such as the internet of things (IoT), VANETs, and cloud computing. With the growing demand for luxury cars, and people's need for safety, the ad-hoc car network is experiencing growth. The connectivity between the vehicle is possible using sensor communication among vehicles in the network. For transmitting forthcoming traffic information in case of a vehicle accident, car connectivity plays a vital role to connect to other vehicles so that appropriate actions can be taken. In this chapter, applications, protocols, trust models, and challenges of VANETS are discussed. The purpose of this chapter is to discuss and elaborate on various aspects related to VANETs and IoT. In addition, the chapter discusses characteristics, challenges, and security concerns in VANETs-based applications.

Artificial intelligence is a huge part of the healthcare industry, having applications and uses in oncology, cardiology, dermatology, and many other fields. Another area where AI is constantly attempting to improve is mental healthcare by integrating machine learning to evaluate data generated by mobile and IoT devices. AI aids in the diagnosis and tailoring of therapy for mentally ill individuals at various stages. The artificial intelligence and machine learning methods utilize electronic health records, mood rating scales, brain images, mobile devices monitoring data in prediction, classification, and grouping of mental health issues, mainly psychiatric illness, suicide attempts, schizophrenia, and depression. The goal of this chapter is to review the literature on artificial intelligence and machine learning algorithms for detecting a person's mental health by utilizing patient health records. In addition, the chapter explains the use of artificial intelligence in curing and monitoring a patient with mental illness through telemedicine.