Chronic diseases quickly become broader public health issues because of the difficulty in obtaining appropriate, often long-term health care. So that, it requires the extension of health care for patients with chronic diseases beyond the clinic to include patient’s home and work environment. To reduce costs and provide more appropriate healthcare, we need telehealth care where internet of things (IoT) technology plays an important role. The integration of the IoT and medical science offers opportunities to improve healthcare quality, and efficiency and to better coordinate healthcare delivery at home and in the workplace. In this paper, we present the realization of a remote healthcare system based on the IoT technology. The function of this system is the transmission via a gateway of internet collected data using biomedical sensors node based Arduino board (e.g., temperature, electrical activity of the heart, heart rate monitor). These data will be stored automatically in a cloud. The health can then be monitored by the doctor or patient using a web page in real-time from anywhere at any time in the world using laptops or smart phones, etc. This method also reduces the need for direct interaction between doctor and patient.
The Internet of Things (IoT) is a new, ongoing revolution. It often uses wireless sensor network (WSN) technologies because these technologies are among the most important solutions for monitoring and controlling the systems. This article provides a model of a smart greenhouse. In this regard, the main contribution of this paper is an innovative implementation of a micro-climate controlled environment for optimal plant growth, based on loT technology and using a fuzzy logic controller. Using this system, we attempted to optimize the functionality of the system proposed by exploiting an Arduino UNO board for data acquisition and processing. The input variables are analog values captured by ZigBee wireless network sensors that are then processed using fuzzy logic control software with heating and extractor control signals. At the same time, all data were sent to the server through a Wi-Fi internet connection, which permitted remote monitoring and analysis of the data via a web browser with tablets, smartphones, and laptops. Results show that the choice of a fuzzy logic controller could promote a comfortable greenhouse micro-climate. Also, we showed the efficiency of our proposed solution for greenhouse climate remote monitoring anywhere via IoT technology.
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