Abstract:

In today's modern world, laboratories have become indispensable parts of education life, business life and daily life in schools, hospitals and many institutions. Whether laboratories are used in the field of education, health or industry, the most basic principle should be to ensure the safety of employees and the environment. The foremost security measures are monitoring, following and keeping the physical (temperature, humidity), chemical (gases), biological (bacteria, viruses) environmental parameters that directly affect human health and that have to be in the environment due to the nature of the laboratories under control. Keeping these parameters under control in laboratory environments is either not done at all or is still done with classical and conventional methods. In this study, a sensor-based system was established in order to eliminate the disadvantages of classical methods with the aim of continuous monitoring of laboratory environment parameters. The proposed sensor-based system is semantically enriched with semantic web technologies. Thus, the efficiency and sustainability of the proposed system has been increased. To effectively control and prevent the spread of diseases such as Covid19, which has affected the whole world in recent years and is transmitted by air, it is essential to monitor and improve the air quality of indoor environments. The proposed study has a high potential to be used in critically important areas such as hospitals, schools, public transport and intensive care units, especially during epidemic times such as Covid-19. By adding artificial intelligence approaches to the proposed system in future studies, the system will gain the ability to predict air quality for the future. Thanks to the developed system, institutions and companies will be able to put their action plans into action earlier and gain an advantage in terms of the manageability of environmental conditions.

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