# Context-Aware System for Information Flow Management in Factories of the Future
## 5 Conclusions and Future Work  
This article presents and discusses the development of a context-aware application called _Context Engine_. Initially, a theoretical study on this type of application is presented. This study enables reaching the conclusion that contextual applications can perform various functions and that, when applied in the manufacturing industry, they aim to generate intelligent information for workers. Such information enables them to respond to manufacturing processes in an instructed and informed way. The Context Engine architecture was designed taking into account the operational scenario, the functions it performs, the previous study on this type of application in the article [34], as well as the CA-FoFS architecture. Divided into three main components--_Context Acquisition_, _Context Builder_ and _Context Server_--according to the different capabilities they have, the architecture makes it possible to modify and add functionality independently, which is crucial given that it is still in a prototype state. By using microservices technology, a choice justified by its flexibility, modularity and evolution, the application is able to adapt to changes and incorporate new features independently. In addition, the use of this technology allows efficient integration and communication between services via APIs, which was crucial in the development of the application. Once the applications had been developed, their functionalities were tested in each application in a laboratory environment and showed their correct functioning and development. Once the applications had been developed, their functionality was tested in a laboratory environment using unit and functional tests. 61 unit tests were carried out on the Context Engine components and all passed, confirming that the services tested behaved as expected and provided responses as predicted. As for the functional tests, all the functionalities provided by Context Engine were tested in each application, integrating them with services that simulate the integration and services layer. All the functionalities were found to be working correctly. As prospects for future work, there are several tasks that can be incorporated into this application, given the extensive range of functionalities that this type of application is capable of performing. One particularly intriguing and essential initiative for production environments would be the integration of _Context Acquisition_ with IoT devices to process data in real time and generate valuable information for the company. Various IoT devices, such as temperature, humidity, pressure and vibration sensors, among others, could be applied in the company. The information from these sensors could be received and processed by _Context Acquisition_ and used to monitor environmental conditions in production areas, ensuring that they are suitable for production, for workers or even to carry out preventive maintenance on machines. In addition, the application's information provision functionalities can be extended. For example, functionalities relating to crucial information such as stock levels, the location of parts in the factory and production estimates could be incorporated. This expansion of functionalities would not only offer more comprehensive support for decision-making, but would also contribute to optimizing processes and improving the overall performance of the production environment. Finally, security rules need to be defined and implemented in the application to guarantee data integrity and protection. Given the current emphasis on the architecture and functionality of the application, the issue of security has been left open to be dealt with at a later date. It will be necessary to carry out a comprehensive analysis of security measures for future iterations and enhancements of communications between the Ca-FoFs system and the Context Engine, ensuring that they comply with appropriate security standards. **Author Contributions:** Conceptualization, A.R. and T.P. ; methodology, R.P.