An efficient IoT based biomedical health monitoring and diagnosing system using myRIO

With the growing and aging population, patient auto monitoring systems are becoming more popular. Smart sensors linked with the internet of things (IoT) make patients' auto monitoring system possible. Nowadays myRIO with LabVIEW is more popular for easy data acquisition, instrument control, and automation. This paper proposed myRIO and IoT based health monitoring and diagnosing system (HMDS) to acquire heartbeat rate, pulse, blood pressure (BP), temperature and activities of the patient using various smart sensors with more accuracy. The acquired raw data from the various sensors had been sent to the myRIO using ESP 8266 Wi-Fi module. The received raw data by the myRIO would be processed to the equivalent medical parameters using LabVIEW and the same might be transferred to the remote monitoring system (RMS) using cloud via a gateway. The abnormalities in the obtained data would be monitored and the diagnosis was made. The experimental setup was developed using various wearable sensors, ESP 8266, myRIO with LabVIEW and cloud with the gateway

Improving stability of utility-tied wind generators using dynamic voltage restorer

The generation of electricity using wind power is significantly increasing and has received considerable attention in recent years. One important problem with the induction generator based wind farms is that they are vulnerable to voltage disturbances and short circuit faults. Any such disturbance may cause wind farm outages. Since wind power contribution is in considerable percentage, such outages may lead to power system stability issues and also violate the grid code requirements. Thus, improving the reliability of wind farms is essential to maintain the stability of the system. The proposed strategy is to use Dynamic Voltage Restorer (DVR), which is one of the promising devices to compensate the voltage disturbance and to improve the stability of the system. It provides the wind generator with the fault ride through capability and improves the reliability of the system. Extensive simulation results are included to illustrate the operation of DVR and fault compensation

Tight Junction-Related Barrier Contributes to the Electrophysiological Asymmetry across Vocal Fold Epithelium

Electrophysiological homeostasis is indispensable to vocal fold hydration. We investigate tight junction (TJ)-associated components, occludin and ZO-1, and permeability with or without the challenge of a permeability-augmenting agent, histamine. Freshly excised ovine larynges are obtained from a local abattoir. TJ markers are explored via reverse transcriptase polymerase chain reaction (RT-PCR). Paracellular permeabilities are measured in an Ussing system. The gene expression of both TJ markers is detected in native ovine vocal fold epithelium. Luminal histamine treatment significantly decreases transepithelial resistance (TER) (N = 72, p<0.01) and increases penetration of protein tracer (N = 35, p<0.001), respectively, in a time-, and dose-dependent fashion. The present study demonstrates that histamine compromises TJ-related paracellular barrier across vocal fold epithelium. The detection of TJ markers indicates the existence of typical TJ components in non-keratinized, stratified vocal fold epithelium. The responsiveness of paracellular permeabilities to histamine would highlight the functional significance of this TJ-equivalent system to the electrophysiological homeostasis, which, in turn, regulates the vocal fold superficial hydration

Internet of Things in Sustainable Energy Systems

Our planet has abundant renewable and conventional energy resources but technological capability and capacity gaps coupled with water-energy needs limit the benefits of these resources to citizens. Through IoT technology solutions and state-of-the-art IoT sensing and communications approaches, the sustainable energy-related research and innovation can bring a revolution in this area. Moreover, by the leveraging current infrastructure, including renewable energy technologies, microgrids, and power-to-gas (P2G) hydrogen systems, the Internet of Things in sustainable energy systems can address challenges in energy security to the community, with a minimal trade-off to environment and culture. In this chapter, the IoT in sustainable energy systems approaches, methodologies, scenarios, and tools is presented with a detailed discussion of different sensing and communications techniques. This IoT approach in energy systems is envisioned to enhance the bidirectional interchange of network services in grid by using Internet of Things in grid that will result in enhanced system resilience, reliable data flow, and connectivity optimization. Moreover, the sustainable energy IoT research challenges and innovation opportunities are also discussed to address the complex energy needs of our community and promote a strong energy sector economy

SEASONAL ASSESSMENT OF HYDROGRAPHIC VARIABLES AND PHYTOPLANKTON COMMUNITY IN THE ARABIAN SEA WATERS OF KERALA, SOUTHWEST COAST OF INDIA

The seasonal variation of the hydrographic variables and phytoplankton species in the Arabian Sea waters of the Kerala coast, Southern India was investigated during different seasons. The variables such as pH, temperature, salinity, turbidity and chlorophyll-a contents of water were found to be high during pre-monsoon season and the dissolved oxygen content was minimal. The concentration of nutrients viz., nitrate, phosphate, silicate varied independently. In the study a total of 53 species of phytoplankton were recorded. Their density was higher during the post-monsoon season than during other seasons and the diatoms were found to be the dominant species. The major phytoplankton in terms of frequency and abundance were the species namely, Biddulphia mobiliensis, Chaetoceros curvisetus, Licmophora abbreviata, Skeletonema costatum, Prorocentrum micans and Oscillatoria sp. They showed significant positive correlation with pH, temperature, salinity, nitrate, phosphate and chlorophyll-a contents, whereas turbidity, dissolved oxygen and silicate exhibited significant negative correlation. The Principal Component Analysis (PCA) developed two principal components with 84.74% of total variability in the water quality which separated pre- and post-monsoon periods from the monsoon season on axis I, and pre-monsoon and monsoon periods from post-monsoon on axis II