The chapter delves into the innovations in machine learning techniques and sensor applications that are reshaping the study of human emotion perception and activity recognition. In the framework of Active and Assisted Living (AAL), the author discusses the urgent need to assist individuals, especially those with special needs and the elderly, in order to enhance their quality of life. It opens by emphasizing the value of AAL, which aims to meet the cognitive, affective, and somatic requirements of people with a wide range of disabilities. The complex spatial–temporal context of individuals in smart environments is characterized by using a strong knowledge representation technique, such as ontologies or conceptual models. This facilitates effective thinking processes for identifying the best assistance options for a given person. Human activity recognition and emotion perception using many sensors are also explored in this chapter, from more traditional machine learning models to novel deep learning approaches. These techniques use multimodal sensors, including those that can’t be seen, to decode complicated human actions. As an example of the breadth of recent developments in sensor technology, we examine in depth the use of invasive, noninvasive, and covert sensors for emotion recognition. Insights into the possibilities of novel ways to identify the human essence through the integration of machine learning and sensor applications are provided in this chapter. Researchers, practitioners, and technologists are inspired to work together and create to better AAL and the human experience as a whole into action for Quality of life (QoL).