# PISIoT: A Machine Learning and IoT-Based Smart Health Platform for Overweight and Obesity Control
## 1 Introduction  
Worldwide obesity has nearly tripled since 1975. In 2016, more than 1.9 billion adults aged 18 years and older were overweight, and of these, over 650 million were obese. In percentage terms, 39% of adults aged 18 years and over were overweight, and 13% were obese. In addition, 41 million children under the age of 5 were overweight or obese, and over 340 million children and adolescents aged 5 to 19 were overweight or obese. Most of the world's population lives in countries where being overweight and obese kills more people than being underweight. Overweight and obesity are defined as abnormal or excessive fat accumulation that impairs the health, productivity, and quality of life of people all over the world [1]. Likewise, the body mass index (BMI) is a simple weight index that takes into account height to determine overweight and obesity in adults. For adults, the BMI provides the most useful population-level measure of overweight and obesity, as it is the same for both sexes and all ages. Although considered characteristic of developed countries, this health problem is increasingly prevalent in underdeveloped countries, especially in urban environments. The fundamental cause of obesity and overweight is an energy imbalance between calories consumed and calories burned. Globally, people have increased their intake of energy-dense foods that are high in fat and engage inlittle or no physical activity due to the increasingly sedentary nature of many forms of work, changes in modes of transport, and growing urbanization. Fortunately, overweight and obesity, as well as their related noncommunicable diseases, are preventable [1]. Similarly, population aging has become significant due to its relationship with globalization, and especially with demographic change. Nowadays, population aging is of the utmost importance for developed countries, where rates of aging are highest, and it is estimated that in the coming years, the rate of aging will continue to increase [2]. Aging is a life process that, unfortunately, is associated with certain complications and diseases, in addition to pathologies that begin in childhood and continue in old age. In this sense, there is a trend toward an increasing population of older adults due to increased life expectancy, which has contributed to a rise in various diseases [3]. In addition, it is estimated that chronic noncommunicable diseases in older adults will tend to increase in coming years, as will healthcare costs, because these types of conditions are long-lasting and require treatment based on technologies, costly medication, and long and frequent periods of hospitalization, without any guarantee that this will prolong the life of older adults or improve their quality of life. This situation generates greater demand for health services by this population group, which has special needs that must be met [4]. On the other hand, it is important to point out that the older adults' health conditions are mainly related to poor dietary habits, lack of physical activity, and addictions--mostly smoking and alcoholism [5]. This increase in longevity and chronic diseases has, along with other external causes, displaced communicable diseases as the main cause of death. Therefore, comprehensive actions are required for the prevention, detection, and timely treatment of various conditions such as overweight and obesity, which affect the health and quality of life of older adults [2]. In the IoT, healthcare is an important application area, because it helps to reduce costs and improve service quality. In addition, biomedical devices or sensors are used in the IoT to monitor biomedical variables such as heart rate, blood glucose level, blood pressure, and body temperature. The IoT's current influence on healthcare is mainly due to the advances that have been made in terms of communications, sensors, and technologies for information processing, and in particular, the advent of wearables (portable body sensors) for real-time monitoring of parameters or biomedical variables [6].