IoT-based real-time poultry monitoring and health status identification

2018 ◽  
Author(s):  
A. Arun Gnana Raj ◽  
J. Gnana Jayanthi
Keyword(s):  
Health Status ◽  
Real Time

scholarly journals Traffic sensor health monitoring using spatiotemporal graphical modeling

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Linjiang Wu ◽  
Chao Liu ◽  
Tingting Huang ◽  
Anuj Sharma ◽  
Soumik Sarkar
Keyword(s):  
Health Status ◽  
Real Time ◽  
Sensor Network ◽  
Health Monitoring ◽  
Series Data ◽  
Spatiotemporal Pattern ◽  
Graphical Modeling ◽  
Traffic Sensors ◽  
Wide Range ◽  
Sensor Health

Accurate traffic sensor data is essential for traffic operation management systems and acquisition of real-time traffic surveillance data depends heavily on the reliability of the traffic sensors (e.g., wide range detector, automatic traffic recorder). Therefore, detecting the health status of the sensors in a traffic sensor network is critical for the departments of transportation as well as other public and private entities, especially in the circumstances where real-time decision is required. With the purpose of efficiently determining the sensor health status and identifying the failed sensor(s) in a timely manner, this paper proposes a graphical modeling approach called spatiotemporal pattern network (STPN). Traffic speed and volume measurement sensors are used in this paper to formulate and analyze the proposed sensor health monitoring system and historical time-series data from a network of traffic sensors on the Interstate 35 (I-35) within the state of Iowa is used for validation. Based on the validation results, we demonstrate that the proposed approach can: (i) extract spatiotemporal dependencies among the different sensors which leads to an efficient graphical representation of the sensor network in the information space, and (ii) distinguish and quantify a sensor issue by leveraging the extracted spatiotemporal relationship of the candidate sensor(s) to the other sensors in the network.

Monitoring driver health status in real time

2020 ◽  
Vol 91 (3) ◽  
pp. 035110
Author(s):  
Fayssal Hamza Cherif ◽  
Lotfi Hamza Cherif ◽  
Mohammed Benabdellah ◽  
Georges Nassar
Keyword(s):  
Health Status ◽  
Real Time

scholarly journals Design of the VRLA Battery Real-Time Monitoring System Based on Wireless Communication

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4350
Author(s):  
Rui Lu ◽  
Jiwu Lu ◽  
Ping Liu ◽  
Min He ◽  
Jiangwei Liu
Keyword(s):  
Health Status ◽  
Wireless Communication ◽  
Real Time ◽  
Monitoring System ◽  
Internal Resistance ◽  
Real Time Monitoring ◽  
Single Function ◽  
Communication Module ◽  
Remaining Capacity ◽  
Vrla Battery

The VRLA (valve-regulated lead-acid) battery is an important part of a direct current (DC) power system. In order to resolve issues of large volume, complicated wiring, and single function for a battery monitoring system at present, we propose to build a novel intelligent-health-monitoring system. The system is based on the ZigBee wireless communication module for collecting voltage, temperature, internal resistance, and battery current in real-time. A general packet radio service (GPRS) network is employed for interacting data with the cloud-monitoring platform. The system can predict the remaining capacity of the battery combined with the software algorithm for realizing real-time monitoring of the battery’s health status and fault-warning, providing a basis for ensuring the safe and reliable operation of the battery. In addition, the system effectively integrates most of the circuits of the battery status collector onto one chip, which greatly reduces the size and the power consumption of the collector and also provides a possibility for embedding each VRLA battery with a chip that can monitor the health status during the whole life. The test results indicate that the system has the characteristics of real-time monitoring, high precision, small-volume, and comprehensive functions.

Study on Multi-Parameter Monitoring Instrument Based on GSM Network

2012 ◽  
Vol 591-593 ◽  
pp. 1854-1857
Author(s):  
Ge Hua Chen ◽  
Yi Zheng Liu
Keyword(s):  
Health Status ◽  
Body Temperature ◽  
Real Time ◽  
Emergency Treatment ◽  
Specific Location ◽  
Gps Positioning ◽  
End Products ◽  
Gsm Network ◽  
Detection Instrument ◽  
Parameter Monitoring

A wireless real-time detection instrument for human health status based on GSM Network is presented. It can real-time monitor the ECG, pulse rate, oxygen saturation, body temperature and other parameters of human body. It has its own characteristics in being small and easy to carry with. Since the coverage of GSM network is broad and inexpensive, the real-time monitoring data of this instrument will be sent to the hospital or ambulance station. If there are any anomalies, the automatic SMS will be sent to patient’s family members, and an emergency telephone will be dialed to win the valuable time of the rescue. The high-end products with GPS positioning function can automatically inform the specific location of the patient, and the patient can be helped in the shortest time for emergency treatment in the case of his loss of active consciousness.

scholarly journals Wearable Sensor Application for Integrated Early Warning and Health Surveillance

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Lauren E Charles ◽  
Devin P Wright ◽  
Zhuanyi Huang ◽  
Cree White ◽  
Fnu Anubhav ◽  
...  
Keyword(s):  
Health Status ◽  
Real Time ◽  
Early Warning ◽  
Wearable Sensors ◽  
Environmental Parameters ◽  
Sensor Data ◽  
Wearable Sensor ◽  
Physiological Strain ◽  
Strain Index ◽  
Physiological Strain Index

Objective: The Wearable Sensor Application developed by Pacific Northwest National Laboratory (PNNL) provides an early warning system for stressors to individual and group health using physiologic and environmental indicators. The application integrates health monitoring parameters from wearable sensors, e.g., temperature and heart rate, with relevant environmental parameters, e.g., weather and landscape data, and calculates the corresponding physiological strain index. The information is presented to the analyst in a group and individual view with real-time alerting of abnormal health parameters. This application is the first of its kind being developed for integration into the Defense Threat Reduction Agency's Biosurveillance Ecosystem (BSVE).Introduction: Wearable devices are a low cost, minimally invasive way to monitor health. Sensor data provides real-time physiological indictors of an individual’s health status without the requirement of health care professionals or facilities. Information gleamed from wearable sensors can be used to better understand physiological stressors and prodromal symptoms. In addition, this data can be used to monitor individuals that are in high risk of health-related problems.However, raw data from wearable sensors can be overwhelming to process and laborious to monitor for an individual and, even more so, for a group of individuals. Often specific combination of ranges of sensor readings are indicative of changes to health status and need to be evaluated together or used to calculate specific signal parameters. In addition, the environment surrounding the individual needs to be considered when interpreting the data. To address these issues, PNNL has developed an application that collects, analyzes, and integrates wearable sensor data with geographic landscape and weather information to provide a real-time early alert and situational awareness tool for monitoring the health of groups and individuals.Methods: The prototype application described here was a product of PNNL’s BSVE Application Development Competition. The final product that will be deployed in the BSVE is currently under development by PNNL and will vary slightly in the exact design and architecture described.Data. Wearable sensor data was collected from the Rim2Rim (R2R) Watch Study of individuals hiking the Grand Canyon in Arizona [1]. Weather information was obtained from nearby weather stations and mapping features were derived from Google Maps.Calculations. A physiological Strain Index (PSI) was calculated using core temperature estimates derived through a Kalman Filter approach and heart rate [2,3].Application. The prototype backend application development was based in Python with a MongoDB. The front-end development was built using a scalable architecture and modular approach with components in React and D3.Results: A prototype application was developed this past summer through the PNNL BSVE App Competition (Fig 1). The application was aimed at visualizing wearable sensor data from the Grand Canyon R2R hike dataset. Simulated real-time analysis was used to calculate health status of individuals hiking based on measured physiological parameters and to alert to individuals with signs of physiologic health stress. Visualization tools were incorporated to enable sensor data for individuals and the group to be viewed simultaneously along with pertinent weather, geographic, and elevation data.Many features described in the prototype application will be incorporated into the final BSVE application. The key changes will be 1) the ability to select given time periods for viewing historical data as well as the real-time data collection, 2) environmental data and map view will come from BSVE internal data sources, and 3) the alerts will provide more information and have their own page for reviewing.Conclusions: The Wearable Sensor Application developed by PNNL for integration into the BSVE provides an early warning system for individual and group health using physiologic and environmental parameters. The application highlights health status from wearable sensors and relevant environmental parameters while monitoring a calculated physiological strain index. With this tool, an analyst can easily monitor the health of individuals and groups with the aid of real-time alerting tool for early detection of abnormal health parameters.

An Intelligent Wearable Platform for Real Time Pilot's Health Telemonitoring

2008 ◽  
pp. 777-784
Author(s):  
Christos Papadelis ◽  
Chrysoula Kourtidou-Papadeli ◽  
Fotini Lazaridou ◽  
Eleni Perantoni
Keyword(s):  
Health Status ◽  
Real Time ◽  
Vital Signs ◽  
Health And Safety ◽  
National Research Council ◽  
Pilot Performance ◽  
Clustering Techniques ◽  
Knowledge Based ◽  
Pressure Changes ◽  
User Friendly

Aviators engage in a variety of outdoor activities where their health status, the environment, and the degree of workload and fatigue affect their performance. An innovative tool has been developed, which supports the real-time health monitoring of pilots using new algorithms based on intelligent clustering techniques for the recognition of possible health problems in flight. The Smart Profiler and the Intelligent Advisor modules of this system exploit the use of knowledge based expert systems and intelligent classification techniques. Coupled with the Portal, which also exploits the use of intelligent clustering techniques, it estimates the pilot’s performance in unknown environments. The new system targets recognizing possible problems at the time of flying, but it can also be used for the monitoring of the pilot performance and progress throughout a period of time, as it stores information from different flying sessions. The system was applied in 20 private pilots during the flight of a Cessna 152 aerobatic. The device was reliable and user-friendly, enabling us to monitor real-time health status of aviators in order to detect possible problems caused by the actual environmental conditions to which individuals are exposed, thus contributing to their health and safety in their working environments. Despite the automation and increasing technological complexity of modern aircrafts, the human operator still plays an important role in controlling those demanding systems. Piloting an aircraft is a highly complex task that requires the pilot to be proficient in numerous skills (Wilson & Eggemeier, 1991) in a hostile environment of cabin pressure changes and circadian rhythm disturbances particularly in long duration flights. The resulting overload of the pilots mandates the need for real time health telemonitoring (Charles, Winget, Charles, De- Roshia, Markley, & Holley, 1984; Denison, Ledwith, & Poulton, 1966; U.S. National Research Council, 2002; Ustinaviciene, Obelenis, & Ereminas, 2004). Real time health telemonitoring would be crucial to early detect and prevent conditions affecting aviator’s vital signs and cognitive performance.

scholarly journals Development of a multiplex real-time PCR surveillance assay for monitoring the health status of Ecuadorian amphibians at risk of extinction

2019 ◽  
Vol 7 (1) ◽  
pp. 674-676
Author(s):  
G. Burgos ◽  
D.A. Narváez-Narváez ◽  
B. Freire-Paspuel ◽  
A. Merino-Viteri ◽  
C. Muslin ◽  
...  
Keyword(s):  
At Risk ◽  
Health Status ◽  
Real Time ◽  
Real Time Pcr ◽  
Risk Of Extinction

scholarly journals Affordable Remote Monitoring of Health Status using Facial Image Processing

2019 ◽  
Vol 8 (12) ◽  
pp. 2518-2521
Keyword(s):  
Image Processing ◽  
Health Status ◽  
Real Time ◽  
Monitoring System ◽  
Remote Monitoring ◽  
High Speed ◽  
Vital Signs ◽  
Close Monitoring ◽  
High Speed Camera ◽  
Remote Monitoring System

This paper presents a real-time monitoring system with a novel approach to assess the human health status without the need for using a body sensor. The project mainly targets improving the quality of life for those living independently but still require close monitoring. Skin fluctuation of the human face is monitored real time with a high-speed camera to determine vital signs including the heart rate and blood pressure. A few image processing algorithms have been utilized to determine the image fluctuations and extract the related features and acquire vital signals. An algorithm assesses and evaluates the risks involved in irregular behaviors and takes follow up actions where required. The application has been implemented on two platforms and interfaced with a high-speed camera to evaluate the performance of the remote monitoring system in indoor situations.

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