The rapid advancements in information and communications technologies (ICT) and the increasing number of smart things shift an old-fashioned healthcare system to a model better suited for a population of the 21st century. New healthcare approaches based on Internet of Things (IoT)/Internet of Medical Things (IoMT) powered systems make health monitoring, diagnostics and treatment more personalized, timely and convenient, enabling a global approach to the healthcare system infrastructure development. Commercial systems in this area exist in various forms but usually do not fit the general patient needs, and those that do are usually economically unacceptable due to the high operational and development costs. Do It Yourself (DIY) healthcare, including mobile applications and consumer medical devices, nowadays is the top healthcare trend. Therefore, this paper, based on well-known low-cost technologies, presents a DIY IoMT solution for observing human vital parameter as well as environmental factors affecting health.

Development of new technologies, particularly the Internet and Sensor Networks, creates a completely new paradigm of the Internet utilization, commonly known as “The Internet of Things (IoT)”. The IoT can be defined as a worldwide network of “smart things” enabled to interact and communicate to each other, as well as with the environment, empowering better understanding of the “real/physical world” and discovering and extracting information about objects and actions that drive that world. Sensor nodes today can be looked as smart objects and therefore they can produce significant computational power which can be used for manipulating and processing collected information. Energy and power efficiency are essential factors in the design and operation of sensor nodes and there are a number of initiatives and tendencies to improve the power efficiency in variety of areas. Relying on the fact that the choice of control algorithm and location of the computational logic may strongly influence power efficiency, in this paper a prototype sensor node, empowered by using fuzzy logic in decision making process, is built and tested in real case environment scenario. Used fuzzy logic processing algorithm is based on predefined rules and can detect a temperature changes in order to ensure accurate and timely response in the case of fire presence. Comparative analysis of power efficiency has been done, and was carried out for best, worst and average case of timely depended temperature changes. The aim of the experiment is to show which solution is the optimal in the sense of energy consumption – implementation of computational logic on sensor node or on a remote host.

The recent proliferation of global networking has an enormous impact on the cooperation of smart elements, of arbitrary kind and purpose that can be located anywhere and interact with each other according to the predefined protocol. Furthermore, these elements have to be intelligently orchestrated in order to support distributed sensing and/or monitoring/control of real world phenomena. That is why the Internet of Things (IoT) concept raises like a new, promising paradigm for Future Internet development. Considering that Wireless Sensor Networks (WSNs) are envisioned as integral part of arbitrary IoTs, and the potentially huge number of cooperating IoTs that are usually used in the real world phenomena monitoring and management, the reliability of individual sensor nodes and the overall network performance monitoring and improvement are definitely challenging issues. One of the most interesting real world phenomena that can be monitored by WSN is indoor or outdoor fire. The incorporation of soft computing technologies, like fuzzy logic, in sensor nodes has to be investigated in order to gain the manageable network performance monitoring/control and the maximal extension of components life cycle. Many aspects, such as routes, channel access, locating, energy efficiency, coverage, network capacity, data aggregation and Quality of Services (QoS) have been explored extensively. In this article two fuzzy logic approaches, with temporal characteristics, are proposed for monitoring and determining confidence of fire in order to optimize and reduce the number of rules that have to be checked to make the correct decisions. We assume that this reduction may lower sensor activities without relevant impact on quality of operation and extend battery life directly contributing the efficiency, robustness and cost effectiveness of sensing network. In order to get a real time verification of proposed approaches a prototype sensor web node, based on Representational State Transfer (RESTful) services, is created as an infrastructure that supports fast critical event signaling and remote access to sensor data via the Internet.

The main goal of soft computing technologies (fuzzy logic, neural networks, fuzzy rule-based systems, data mining techniques...) is to find and describe the structural patterns in the data in order to try to explain connections between data and on their basis create predictive or descriptive models. Integration of these technologies in sensor nodes seems to be a good idea because it can significantly lead to network performances improvements, above all to reduce the energy consumption and enhance the lifetime of the network. The purpose of this paper is to analyze different algorithms in the case of fire confidence determination in order to see which of the methods and parameter values work best for the given problem. Hence, an analysis between different classification algorithms in a case of nominal and numerical data sets is performed with the goal to realize which of applied techniques obtain higher accuracy and less error