## 2 Related Works
Although the system used some reactive components, the strategies or mechanisms to achieve scalability and availability of the system in an environment with a large number of users were not explained. An end-to-end framework for big data storage and analysis for batch and real-time processing in the context of an ECG monitoring application was presented in [21]. The system was designed in the context of Amazon Web Services with products owned by Amazon. However, the implementation lacks the flexibility to handle containers with open-source products. On the other hand, the architecture did not incorporate DevOps practices for CI/CD of the services that are of interest to the developers of the system. Furthermore, in relation to systems for the control of food intake, some models of computer systems for the prediction and control of diets have been developed. These systems assign a diet to a person with a particular health condition such as obesity or diabetes [22,23]. An expert system based on an ontology for the care of the nutrition process for elderly people was presented in [22]. The system tests were carried out inside the laboratory to validate an inference engine to assess the nutrition problems and the comparison of the results provided with those given by the nutritionist. However, the architecture does not present characteristics that allow the scalability of the system, or the real remote monitoring of food intake. The purpose of the research in [23] was only characterized through a zone class of blood potassium levels; monitoring and control were not addressed. Moreover, there are studies related to the control of feeding people for various purposes, mostly for weight control, and some relevant technologies are used in some of them [24,25]. The work in [24] proposed a mobile app to help parents and doctors monitor children who suffer from high obesity rates. The IoT application allows tracking of food intake, remote capture, and constant monitoring of children's data. Although the children send information about the intake through a mobile application to an application server, the intake control is in the nutritionist's hands. Additionally, the mechanisms to provide high scalability and high availability to the system are not addressed. The work reported in [25] presented a model that collects data from sensors and social networks to provide monitoring and to prevent obesity, including tracking food intake, lifestyle, exercise activities, generating warnings, and triggering interventions whenever needed. The real controlled planning of food intake does not arise. Although there are data mining processes, the system does not provide solutions for handling the big data produced by this type of system. Additionally, the components of the monitoring process are highly coupled, and the system does not show evidence of scalability. The objective of our work is to propose an approach to develop cloud-based e-health IoT reactive services as a distributed system for users who work collaboratively in the care of elderly people. Our approach includes the use of architecture with scalability and interoperability between its components. In addition, the use of certain design patterns allows the system to grow flexibly to provide new subsystems for healthcare. Unlike some of the studies discussed above, we promote the use of crowd sensing [5; 26] for collecting data as opposed to using a dedicated infrastructure such as WSANs that are too expensive. The smartphone can act as a gateway that takes data from a wireless body area network (WBAN) through light protocols such as Bluetooth. Additionally, we promote the use of the MQTT protocol incorporated into smartphones for the exchange of messages with other parts of the system. The use of a certain type of fast data architecture has been used minimally without enhancing its usefulness. As part of our system architecture, we built a fast pipeline to obtain real-time monitoring and additional strategies and mechanisms for the interoperability and scalability of its components.