A modular IoT platform for real-time indoor air quality monitoring

The impact of air quality on health and on life comfort is well established. In many societies, vulnerable elderly and young populations spend most of their time indoors. Therefore, indoor air quality monitoring (IAQM) is of great importance to human health. Engineers and researchers are increasingly focusing their efforts on the design of real-time IAQM systems using wireless sensor networks. This paper presents an end-to-end IAQM system enabling measurement of CO2, CO, SO2, NO2, O3, Cl2, ambient temperature, and relative humidity. In IAQM systems, remote users usually use a local gateway to connect wireless sensor nodes in a given monitoring site to the external world for ubiquitous access of data. In this work, the role of the gateway in processing collected air quality data and its reliable dissemination to end-users through a web-server is emphasized. A mechanism for the backup and the restoration of the collected data in the case of Internet outage is presented. The system is adapted to an open-source Internet-of-Things (IoT) web-server platform, called Emoncms, for live monitoring and long-term storage of the collected IAQM data. A modular IAQM architecture is adopted, which results in a smart scalable system that allows seamless integration of various sensing technologies, wireless sensor networks (WSNs) and smart mobile standards. The paper gives full hardware and software details of the proposed solution. Sample IAQM results collected in various locations are also presented to demonstrate the abilities of the system. 2018 by the authors. Licensee MDPI, Basel, Switzerland.Acknowledgments: This publication was made possible by the National Priority Research Program (NPRP) award (NPRP6-600-2-250) from the Qatar National Research Fund (QNRF), a member of the Qatar Foundation. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of QNRF.Scopu

Carbonic anhydrase inhibitor coated gold nanoparticles selectively inhibit the tumor-associated isoform IX over the cytosolic isozymes I and II.

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A smart rig for calibration of gas sensor nodes

Electrochemical gas sensors require regular maintenance to check and secure proper functioning. Standard procedures usually involve testing and recalibration of the sensors, for which working environments are needed. Periodic calibration is therefore necessary to ensure reliable and accurate measurements. This paper proposes a dedicated smart calibration rig with a set of novel features enabling simultaneous calibration of multiple sensors. The proposed calibration rig system comprises a gas mixing system, temperature control system, a test chamber, and a process-control PC that controls all calibration phases. The calibration process is automated by a LabVIEW-based platform that controls the calibration environment for the sensor nodes, logs sensor data, and best fit equation based on interpolation for every sensor on the node and uploads it to the sensor node for next deployments. The communication between the PC and the sensor nodes is performed using the same IEEE 802.15.4 (ZigBee) protocol that the nodes also use in field deployment for air quality measurement. The results presented demonstrate the effectiveness of the sensors calibration rig.Scopu

Impact of time synchronization error on the mode-shape identification and damage detection/localization in WSNs for structural health monitoring

Time synchronization in wireless sensor networks (WSNs) is a critical challenge for any distributed system such as WSNs for structural health monitoring (SHM). In SHM, mode shape identification, damage detection and damage localization are sensitive to time synchronization errors (TSEs). Indeed, the errors, due to the time shift between the incoming raw data from each sensor node, may hugely affect the data integrity and then the mode shape identification of the structure under analysis. In this paper, we characterize the impact of TSE on the modal analysis, damage detection and damage localization using frequency domain decomposition (FDD) implemented in a semi-local manner. In order to decrease the size of the transmitted data by the sensor nodes and reduce the processing load and the needed storage capacity on the central unit, we adopt a semi-local processing approach where each sensor node partially processed data and transmit it to a central unit for further processing such as mode shape identification, damage detection and damage localization. We adopt the model where each sensor node performs the Fast Fourier Transform (FFT) of the measured vibration signal and the transmission of the FFT values to a central unit or to a cluster head for further processing. The results show that TSE has a strong impact on the mode shape identification, damage detection and damage localization. Furthermore, results show that semi-local processing is more sensitive to TSE compared to centralized processing.Scopu

Impact of time synchronization error on the mode-shape calculation in wireless sensor networks for structural health monitoring

For structural health monitoring (SHM), mode shape calculation is an important task that needs to be performed accurately and reliably. The use of wireless sensor networks (WSNs) for SHM is a very effective and a promising solution. However, WSNs experience synchronization errors among the sensor nodes, which can affect the accuracy of the mode shape calculation. In this paper, we study the impact of time synchronization error (TSE) on the mode shape calculation in a semi-local manner using frequency domain decomposition (FDD) implemented in a semi-local manner. In order to decrease the size of the transmitted data by the sensor nodes and reduce the processing load and needed storage capacity on the central unit, we adopt a semi-local processing approach where each node partially processes the measured data. Then, sensor nodes send the partially-processed data to a central unit for further processing and mode shape calculation. Numerical results prove that the time synchronization error has a significant impact on the accuracy of the mode shape calculation. Furthermore, results show that semi-local processing is more sensitive to TSE compared with centralized processing. 2016 IEEE.Scopu

Synthesis and anti-proliferative activity of novel quinolin-8-ol derivatives

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Fuzzy Elliptic Curve Cryptography for Authentication in Internet of Things

The security and privacy of the network in Internet of Things (IoT) systems are becoming more critical as we are still more dependent on smart systems. Considering that packets are exchanged between the end user and the sensing devices, it is then important to ensure the security, privacy and integrity of the transmitted data by designing a secure and a lightweight authentication protocol for the IoT systems. In this paper, in order to improve the authentication and the encryption in IoT systems, we present a novel method of authentication and encryption based on elliptic curve cryptography (ECC) using random numbers generated by fuzzy logic. We evaluate our novel key generation method by using standard randomness tests such as: frequency test, frequency test with mono block, run test, discrete Fourier transform test and advanced discrete Fourier transform test. Our results show superior performance compared to existing ECC based on shift registers. In addition, we apply some attack algorithms such as Pollard’s ρ and Baby-step Giant-step to evaluate the vulnerability of the proposed scheme. IEEEScopu

Key Generation Based Fuzzy Logic and Elliptic Curve Cryptography for Internet of Things (IoT) Authentication

The security and privacy of the network in the Internet of Things is playing an important challenge for researchers and engineers. Considering that packets are exchanged between the end user and the sensing devices, it is then important to ensure the security, privacy and integrity of the transmitted data by designing a secure and a lightweight authentication protocol for the IoT environment. In this paper, we present a novel method of authentication and encryption based on Elliptic Curve Cryptography (ECC) and on random numbers generated by fuzzy logic for the improvement of the authentication and the encryption in IoT systems. We evaluate our novel key generation method using standard randomness tests such as: Frequency test, Frequency test with mono block, run test, discrete Fourier transform test and advanced discrete Fourier transform test. Our results show superior performance. 2020 IEEE.Qatar University;Western University;Industrial Research and Consultancy CentreScopu

Synthesis of substituted N-aryl-N'-sulfamoyl-oxazolidin-2-ones with potential antibacterial activity

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