Fault-Tolerant Temperature Control Algorithm for IoT Networks in Smart Buildings

[EN] The monitoring of the Internet of things networks depends to a great extent on the availability and correct functioning of all the network nodes that collect data. This network nodes all of which must correctly satisfy their purpose to ensure the efficiency and high quality of monitoring and control of the internet of things networks. This paper focuses on the problem of fault-tolerant maintenance of a networked environment in the domain of the internet of things. Based on continuous-time Markov chains, together with a cooperative control algorithm, a novel feedback model-based predictive hybrid control algorithm is proposed to improve the maintenance and reliability of the internet of things network. Virtual sensors are substituted for the sensors that the algorithm predicts will not function properly in future time intervals; this allows for maintaining reliable monitoring and control of the internet of things network. In this way, the internet of things network improves its robustness since our fault tolerant control algorithm finds the malfunction nodes that are collecting incorrect data and self-correct this issue replacing malfunctioning sensors with new ones. In addition, the proposed model is capable of optimising sensor positioning. As a result, data collection from the environment can be kept stable. The developed continuous-time control model is applied to guarantee reliable monitoring and control of temperature in a smart supermarket. Finally, the efficiency of the presented approach is verified with the results obtained in the conducted case study

A Cyber -Physical System for Industrial Air Pollution Monitoring using Raspberry Pi

In this paper the proposed system will focus on the monitoring of air pollutants concentration with the help of combination of Internet of things with wireless sensor networks. The analysis of air quality can be done by calculating air quality index. This information will be displayed on the webpage via internet in real time. By the combination of internet of things and wireless sensor networks for purpose of air pollution monitoring it becomes easy to keep the air quality data updated in real time. Also the system is cost effective which make its installation possible in various areas. The system existing before was based on microcontroller based toxic gas detecting and alerting system and the developing system will have a complete monitoring system which is IOT based. Also the information will be directly sent to the internet from system; no need of computer for transmission purpose which reduces the cost further. The main objective of this system is to monitor air pollution by using internet of things application. Also to obtain cost effective system that will help to keep track of concentration of pollutants in air and find effect of concentration of pollutants on air in terms of air quality index to achieve real time monitoring by continuously updating the data on webpage via internet

Lightweight Synchronization Algorithm with Self-Calibration for Industrial LORA Sensor Networks

Wireless sensor and actuator networks are gaining momentum in the era of Industrial Internet of Things IIoT. The usage of the close-loop data from sensors in the manufacturing chain is extending the common monitoring scenario of the Wireless Sensors Networks WSN where data were just logged. In this paper we present an accurate timing synchronization for TDMA implemented on the state of art IoT radio, such as LoRa, that is a good solution in industrial environments for its high robustness. Experimental results show how it is possible to modulate the drift correction and keep the synchronization error within the requirements

Did Class 1 and Class 2 Aminoacyl Trna Synthetases Descend from Genetically Complimentary, Catalytically Active ATP-Binding Motifs?

The Internet of Things is widely regarded as one of the most disruptive technologies as it inte-grates smart physical objects into the networked society and digital value networks. Today, the Internet of Things has the potential to transform business-to-customer interactions enabled by smart things. Remote patient monitoring, predictive maintenance, and automatic car repair are just a few examples of evolving business-to-thing (B2T) interactions. However, the Internet of Things remains a space low on theoretical investigations. Complementing the tech-nical/engineering focus on the Internet of Things, we developed and evaluated a taxonomy of B2T interaction patterns, building on sociomateriality as justificatory knowledge. We also demonstrated the taxonomy’s applicability and usefulness based on simple and complex real-life objects (e.g., Nest, RelayRides, Uber). Our taxonomy contributes to the descriptive knowledge related to the Internet of Things, as it enables the classification of B2T interactions, providing the basis for sense-making research and early theory-led design. When combining the weak and the strong form of sociomateriality as justificatory knowledge, we also found that the Internet of Things enables and requires a new perspective on material agency, treating smart things as independent actors

Design of a WSN Platform for Long-Term Environmental Monitoring for IoT Applications

The Internet of Things (IoT) provides a virtual view, via the Internet Protocol, to a huge variety of real life objects, ranging from a car, to a teacup, to a building, to trees in a forest. Its appeal is the ubiquitous generalized access to the status and location of any "thing" we may be interested in. Wireless sensor networks (WSN) are well suited for long-term environmental data acquisition for IoT representation. This paper presents the functional design and implementation of a complete WSN platform that can be used for a range of long-term environmental monitoring IoT applications. The application requirements for low cost, high number of sensors, fast deployment, long lifetime, low maintenance, and high quality of service are considered in the specification and design of the platform and of all its components. Low-effort platform reuse is also considered starting from the specifications and at all design levels for a wide array of related monitoring application