Several European statistics confirm that a large number of people have fatal accidents every year in the workplace. For this reason, one of the most important European objectives is to reduce the number of industrial accidents significantly. In fact, one of the European objectives set for 2020 is the 25% reduction in the number of industrial accidents. In order to reduce accidents it is essential to pay attention to the workers, their single workplaces and to their working conditions. In this way, if workers had a safer environment, the number of accidents could be significantly reduced, implying therefore a reduction in costs. Fasys Project, focused on factories of machining and assembly operations, aims to achieve this reduction promoting the use of technologies and giving, at the same time, a principal role to the worker. From now on, the worker, who has represented a neglected element in the factories, will be the center of attention. The increase of his security, and the enhancement of his working conditions and health, will be key elements for the Factory of the Future performance.
For this reason, the future work has to be oriented on new technological applications to get a factory safer and to reduce significantly the number of accidents. To control the accidents it is necessary to anticipate and estimate what can happen. So, prevention is a key point. To manage it, it is important to collect and measure data during a period of time, in order to evaluate their progress. Consequently, the perfect model would be a factory in which the risks and health were controlled at any time. To achieve so, FASyS has different main objectives and one of them (where Tissat is working actively) is to develop a “Health Continuous Vigilance System”. The system includes both the monitoring to characterize workers activity and environment, and aspects related to prevention protocols. To manage it, several systems of collecting data are needed. They can be distributed around the factory and monitor, for example, personal and environment data, or get information, for example, from medical knowledge or previous medical information of the worker. Besides, due to the big amount of generated information (so far a “big data” problem is not reached on the prototype, but it’ll probably appear when moved to more complex environments), intelligent systems for massive data processing are needed. In this way, the information could be easily managed and classified, in order to obtain data from a specific situation that could be required.
Nowadays, the number of sensors for monitoring personal health data is increasing. In addition, sensors that collect environmental parameters in industrial factories are being introduced more and more. The problem encountered so far, and solved in this project, is that these data are not connected. The information is only collected in order to produce isolated diagnosis, but not common results, and the collected data become less relevant if they are not treated together. The final decision, in a dynamic environment like a factory, could be more precise if results came from a study of a diverse set of parameters.

According to FASyS project, the first step to improve the health and safety in factories is to increase the personal and environmental monitored data. Consequently, there is a need to develop a system able to store all this information. So NOMHAD system has been developed.
NOMHAD System

NOMAHD is an application able to stored part of this required information: workers’ personal parameters such as blood pressure, pulse and oxygen saturation. The system performs a prioritization and an intelligent management of alarms. These alarms are based on the rules and protocols accepted by health professionals and by the health system. This service will combine the information, through the prioritized alarm list, with the generation of specific summaries about the state and evolution of the person. This enables a more efficient management of events.

So far, the options managed by NOMHAD are specifically thefollowing:
  • To create a patient. The professional will fill the administrative worker data and the medical relevant data for a future evaluation. Patients will also be assigned to health professionals.
  • Reception and Display of Monitoring. The system stores the monitoring data of the person. It stores them into a database related to the personal health record in order to be used by health professionals in the future. The monitoring data are displayed in the right way, either in graphical form, numerical, image, etc. The data stored in the system are processed on arrival. A set of several rules, defined by the doctor and adapted to the personal profile, are applied. These rules allow the system to detect potential anomalies found in the data, in order to take decisions. For the definition of the rules, health professionals will have a tool to help themselves with this task.
  • To configure alerts. The system will have an alert module that, based on the monitoring data and the limits defined as optimal by a professional, will be able to detect whether the data stored are acceptable or not.
  • The possibility of assigning questionnaires. The patient mood could be extracted from these questionnaires. Health professional will choose the questionnaire and will have the possibility to personalize it depending on the needs of each worker in particular. These questionnaires will be available in the future in case the professionals want a subsequent consulting or validations.
  • Monitoring. The measurements can be obtained with usual external devices, whose information is introduced afterwards in the system or it can be used integrated elements into the system (controlled, for example, by Bluetooth and transmitting the captured data directly to the system). The design of the system can be extended to introduce new devices.
With the purpose of completing the personal data stored in NOMHAD, FASyS project proposes a connection to the current health system. This connection provides a register about the health state of the person during his lifetime, which collects data such as his diseases, surgically interventions or pains. This health system is commonly known as EHR (Electronic Health Record).
Finally, once the information has been monitored and classified, the next point is focused on the intervention. With the aim of representing prevention protocols for this intervention, workflows are developed. Given the workers singularity, the adaptation of the prevention protocols is needed for each one of them. In this way, the elimination of the occupational hazard is much more effective.
Next day we’ll focus on the architecture of the “Health Continuous Vigilance System”, as well as on the prevention protocol workflows implementation.