## 1 Introduction  
Much of the research that has been carried out in the social sciences related to subjective wellbeing (SWB) focuses on its conceptualization, measurement, and understanding [1]. The use of subjective indicators, such as \"happiness\" or \"subjective wellbeing\", has become more prevalent in the last 50 years [2]. The desire to understand what makes a life a good life is a desire that comes from ancient times [3]. We have very little knowledge about what makes a worthwhile life [4]. To date, most of the instruments being used to measure wellbeing are time-consuming methods that are based on self-report to capture qualitative data; they are subjective to the interpretation of social scientists (e.g., sociologists, economists, and urban planners). Accordingly, there is an untapped potential to develop tools that enable specialists to more objectively quantify aspects of wellbeing. It is necessary to understand how to measure people's wellbeing, or, in other words, to understand the factors that affect the self-perception of people's happiness. The literature has shown that opportunistic sensing systems are useful in objectively measuring aspects of health, behaviors, and especially mobility. Most of these studies assume the availability of communications infrastructure and access to innovative technology \"anytime and anywhere\" that is hardly available in undeveloped regions. However,scientific evidence that supports the efficacy of mobile platforms in developing regions for measuring wellbeing is currently lacking. Real-life descriptions of mobile sensing solutions in undeveloped regions are scarce and urgently needed. People's ability to move about in their environment affects how they perceive their wellbeing. Mobility is a critical and essential factor in maintaining life satisfaction and wellbeing in a complex urban society [5]. In other words, external factors, such as access to jobs, public services, and better infrastructure, affect individuals' subjective wellbeing. Limited access to essential services and limited mobility impacts their possibility of escaping poverty [6]. Indeed, geography plays a causal role in determining the economic growth of a household [7]. For example, a poor household located in an area with favorable geographic factors may eventually escape poverty. In contrast, another completely identical home located in an area with less access to these services will see little progress [8]. These challenges are exacerbated in undeveloped regions with low infrastructure development, like Mexico, which may commonly have a poor road infrastructure, such as lack of sidewalks, streets, and pedestrian crossings. Even in countries with observed economic growth, there are persistently poor areas [7]. More than 70% of the 3.3 billion people that make up the global urban population live in environments that are poor in public resources [9]. In Latin America, 260 million people live in the 198 largest cities [10]. This amounts to a little over 40% of the population living in only 198 cities. People with poor access to public resources have to be continually more aware of other factors beyond time and money. Suppose that a person perceives a lack of security during commutes between home, work, school, and other usual places. In that case, it makes her life more difficult, as she has to be more aware of factors that can affect their safety during the mobility decision-making process. This situation ends up affecting their quality of life and their wellbeing. We hypothesize that the mobility divergences that are obtained from individuals' mobility patterns may signal factors that affect and can be used to measure individuals' wellbeing objectively. In this paper, we present our conclusions that resulted from a quantitative analysis that we made on data we obtained from a study tjhat ee carried out in Camino Verde, a disadvantaged area located inside of the city of Tijuana in Baja California, Mexico. The mobility data observed presented divergences.