Our goal was to develop continuous remote sensing, monitoring, and control technology for the structural elements of a specific critical facility that cannot be inspected post-construction without demolition. We aimed to design specialized IoT sensors to measure pressure, displacement, cracks, vibrations, and moisture, and ensure the local power supply for these sensors. The collected data is transmitted via a relay station to a dedicated server, where it is archived. Based on preloaded parameters, the server program executes necessary interventions according to protocol specifications.

Failures due to the aging of critical infrastructure facilities can be challenging to detect locally, especially since current detection tools cannot accurately locate the issue within underground, concrete, or high-placed metal structures. Consequently, resolving such emergency situations often involves significant and time-consuming demolition and construction tasks. Therefore, exceptional attention must be given to the monitoring and operation of these facilities. Current technologies only allow for post-failure management of damages or vandalism, and fixing underground failures is highly costly and sacrificial. Thus, it is crucial to enable preventive examination and monitoring of these structures, a problem yet unsolved with current scientific advancements.

Our sensors integrated into the structural elements, along with the created IoT ecosystem, can detect emerging issues leading to specific failures (such as continuous monitoring of concrete moisture by humidity sensors, structural element status by corrosion detectors, and displacement of static elements by strain gauges). This data assessment allows for determining the intervention level, preventing severe damage. We developed software for the IoT ecosystem that manages intervention levels based on received values, ranging from preventive maintenance to repairs or demolition. The product developed from our prototype carries innovative technical knowledge that provides solutions for infrastructure operators, disaster, and civil protection by facilitating timely detection and precise failure location, significantly reducing intervention costs. Sysman Zrt. successfully implemented the project.

Beneficiary name: Sysman Informatikai Zrt.

Project title: Methodological Research of Intelligent Physiological Monitor

Project identification number: GINOP-2.1.1-15-2015-00251

Contracted grant amount: 386,013,424 HUF

Support rate: 68.5%

Project completion date: 2018.10.31.

Project Description:

The main goal of the project was to conduct methodological research on an intelligent physiological monitor that, by measuring physiological parameters, can diagnose an individual’s health status, draw conclusions, and provide further personalized health, treatment, and lifestyle advice.

The application of the intelligent physiological monitor provides valuable information and assistance not only to patients or elderly users but also eases the daily work of doctors, caregivers, and nurses. In addition to patients and the elderly, professional and amateur athletes, as well as those undergoing rehabilitation, can use the results of the intelligent physiological monitor.

There is an increasing demand and need for healing and healthcare services. This trend is partly due to the growing proportion of the elderly population. Additionally, more and more people are turning towards a healthy lifestyle, health preservation, sports, wellness, and generally towards prophylaxis and disease prevention, adopting a predictive lifestyle. The increasing demand currently significantly exceeds the supply. The solution can only be achieved through the combined research and development of tools and methodologies capable of recording the user’s or patient’s physiological parameters under everyday life conditions and deriving diagnostic and therapeutic conclusions from them.

The intelligent physiological monitor researched within the framework of the project can function as an expert system in various fields of everyday life as well as in institutional medical treatment, relying on an integrated knowledge base and utilizing status indicator information extracted from the patient’s physiological data.