Multilayered fuzzy behavior fusion for real-time reactive control of systems with multiple sensors

1996 ◽  
Vol 43 (3) ◽  
pp. 387-394 ◽  
Author(s):  
S.G. Goodridge ◽  
M.G. Kay ◽  
R.C. Luo
Keyword(s):  
Real Time ◽  
Reactive Control ◽  
Multiple Sensors

Smart Environmental Monitoring System

2019 ◽  
Vol 10 (1) ◽  
pp. 43-54
Author(s):  
Karthik Sudhakaran Menon ◽  
Brinzel Rodrigues ◽  
Akash Prakash Barot ◽  
Prasad Avinash Gharat
Keyword(s):  
Air Pollution ◽  
Real Time ◽  
Urban Areas ◽  
Real Life ◽  
Cloud Service ◽  
Threshold Value ◽  
Time Data ◽  
Multiple Sensors ◽  
Alert Message ◽  
Environmental Monitoring System

In today's world, air pollution has become a common phenomenon everywhere, especially in the urban areas, air pollution is a real-life problem. In urban areas, the increased number of hydrocarbons and diesel vehicles and the presence of industrial areas at the outskirts of the major cities are the main causes of air pollution. The problem is seriously intense within the metropolitan cities. The governments around the world are taking measure in their capability. The main aim of this project is to develop a system which may monitor and measure pollutants in the air in real time, tell the quality of air and log real-time data onto a remote server (Cloud Service). If the value of the parameters exceeds the given threshold value, then an alert message is sent with the GPS coordinates to the registered number of the authority or person so necessary actions can be taken. The Arduino board connects with Thingspeak cloud service platform using ESP8266 Wi-Fi module. The device uses multiple sensors for monitoring the parameters of the air pollution like MQ-135, MQ-7, DHT-22, sound sensor, LCD.

Solar-Powered Environment Monitoring System Based on ARM

2014 ◽  
Vol 641-642 ◽  
pp. 1168-1171
Author(s):  
Ling Long ◽  
Ya Dong Shao ◽  
Hai Shang Liu
Keyword(s):  
Solar Energy ◽  
Real Time ◽  
Intelligent System ◽  
Work Life ◽  
Environment Monitoring ◽  
The Real ◽  
Multiple Sensors ◽  
The Core ◽  
Solar Powered ◽  
Monitoring Information

In order to accurately obtain the real-time environment information, this paper introduces a solar energy environmental monitoring intelligent system, and gives the corresponding design of hardware and software flow. The system adopts solar energy to supply power, uses ARM as the core microprocessor, and acquires environment information by multiple sensors, so that system terminal displays the real-time monitoring information. This design not only enhances Security for people's work, life and travel, but also makes full use of solar energy to achieve a modern green life.

scholarly journals Near-Real-Time Tephra Fallout Assessment at Mt. Etna, Italy

2019 ◽  
Vol 11 (24) ◽  
pp. 2987 ◽  
Author(s):  
Simona Scollo ◽  
Michele Prestifilippo ◽  
Costanza Bonadonna ◽  
Raffaello Cioni ◽  
Stefano Corradini ◽  
...  
Keyword(s):  
Real Time ◽  
Satellite Images ◽  
Low Cost ◽  
Column Height ◽  
Explosive Eruptions ◽  
Volcanic Plume ◽  
Emergency Responders ◽  
Multiple Sensors ◽  
New System ◽  
Tephra Fallout

During explosive eruptions, emergency responders and government agencies need to make fast decisions that should be based on an accurate forecast of tephra dispersal and assessment of the expected impact. Here, we propose a new operational tephra fallout monitoring and forecasting system based on quantitative volcanological observations and modelling. The new system runs at the Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo (INGV-OE) and is able to provide a reliable hazard assessment to the National Department of Civil Protection (DPC) during explosive eruptions. The new operational system combines data from low-cost calibrated visible cameras and satellite images to estimate the variation of column height with time and model volcanic plume and fallout in near-real-time (NRT). The new system has three main objectives: (i) to determine column height in NRT using multiple sensors (calibrated cameras and satellite images); (ii) to compute isomass and isopleth maps of tephra deposits in NRT; (iii) to help the DPC to best select the eruption scenarios run daily by INGV-OE every three hours. A particular novel feature of the new system is the computation of an isopleth map, which helps to identify the region of sedimentation of large clasts (≥5 cm) that could cause injuries to tourists, hikers, guides, and scientists, as well as damage buildings in the proximity of the summit craters. The proposed system could be easily adapted to other volcano observatories worldwide.

scholarly journals Design Secure WSN with Advancement in Finding Rouge Access Point with Soft Computing Tools

2020 ◽  
Author(s):  
Abhijit S. Bodhe ◽  
Pravin Dhanrao ◽  
Abhimanyu Sangle ◽  
Jagdisha N.
Keyword(s):  
Real Time ◽  
Soft Computing ◽  
Fuzzy Controller ◽  
Access Point ◽  
Wireless Sensor ◽  
Time Data ◽  
Potential Threat ◽  
Biometric Data ◽  
Multiple Sensors ◽  
Secure Information

Now a days wireless communication is become very vast, important and easy to access with multiple wireless sensor network in existence as it having very less cost associated and easily available via multiple mobile devices with sensors to create a hotspots, It creates a potential threat for community using wireless media for communicating some secure information like banking passwords, military information, biometric data etc. on unsecured network. This proposed paper will expose one of such potential threat Rouge Access Point (RAP) detection by making the use of soft computing prediction tool in our case fusion of neural network with fuzzy logic known as neuron-fuzzy method and design a fuzzy controller (FLC) to find such RAP & secure the existing wireless network where multiple sensors are actively working in real time to provide the real time data.

scholarly journals IoT based Water Management System

2019 ◽  
Vol 7 (9) ◽  
pp. 24-33
Author(s):  
Prof. R. R. Karhe ◽  
Ms.Vaishali Dilip Kachawa
Keyword(s):  
Real Time ◽  
Conventional Technique ◽  
Measuring System ◽  
Monitoring And Control ◽  
Control Approach ◽  
Multiple Sensors ◽  
Quality Of Water ◽  
True Time ◽  
Increasing Demand

The conventional technique of measuring the quality of water is to gather the samples manually and send it laboratory for analysis, but this technique is time overwhelming and not economical. Since it is not feasible to take the water sample to the laboratory after every hour for measuring its quality. The water quality measuring system can measure the essential qualities of water in real time. The system consists of multiple sensors to measure the standard of water, microcontroller and wifi modem to send the information to the watching center. It's a true time system which is able to endlessly measure the standard of water and can send the measured values to the watching center when each predefinedtime. During the past decade, water needs have increased unpredictably in India. Increasing demand of water supply has become a major challenge for the world. Wasteful usage of water, climatic changes and Urbanization has further depleted the resource. Conservation and management of the resource must be given utmost importance. In this paper, we present an IoT design for water monitoring and control approach which supports internet based data collection on real time bases. This paper proposes a system that addresses new challenges in the water sector -flow rate measuring and the need for a study of the supply of water in order to curb water wastage and encourage its conservation. We also measure the quality of water distributed to every household by deploying pH and conductivity sensors. The traditional water metering systems require periodic human intervention for maintenance making it inconvenient and often least effective. This system is designed to overcome for shortcoming of the existing models for a ubiquitous usage of wireless systems for smart quality monitoring and communicate datawirelessly.

Real-Time Well Monitoring and Engineering Analysis of Drilling Activities: Intelligent Rig State Detection and Prediction With Uncertainty

2020 ◽  
Author(s):  
Vanessa Kemajou ◽  
Robello Samuel
Keyword(s):  
Real Time ◽  
Forecast Model ◽  
Engineering Calculation ◽  
Open Architecture ◽  
Engineering Analysis ◽  
Time Data ◽  
Multiple Sensors ◽  
Real Time Data ◽  
Drilling Quality ◽  
Drilling Operations

Abstract Drilling activities are risky and costly, especially when performed offshore. Careful monitoring and real time data analysis are required for safe and efficient operations with minimized down-time. Drilling operations, being fast-paced and not visible, often lead to transient and unforeseen issues. The synchronous assessment and prediction of drilling quality has historically been a challenge. It relies on a prompt collection, analysis and prediction of the multiple sensors data, as well as an immediate comparison to the original drilling plan. Another challenge is achieving real-time well engineering, and automatically and instantaneously providing valuable insights to the engineering and operations teams. A system was successfully developed to tackle these challenges. It is a cloud-based application, made with an event-driven streaming architecture to automatically retrieve real-time drilling data and compare it with planned data. The real-time data is automatically made available to determine the current well operation or rig state, and trigger the subsequent engineering analysis. Next, a forecast model is trained with the engineering calculation outputs and it returns predictions on these outputs while considering their inherent uncertainty. As a result, these predictions enable alerts to be sent when the system detects approaching anomalous conditions. The proposed system is a DecisionSpace® 365 cloud-native application on an open architecture. It is flexible, accessible from anywhere, can be automatically updated for continuous improvement, and can be deployed easily and quickly. It can also be extended to further applications.

scholarly journals Designing an Efficient Emergency Response Airborne Mapping System with Multiple Sensors

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Chaoyong Shen ◽  
Zongjian Lin ◽  
Shaoqi Zhou ◽  
Xuling Luo ◽  
Yu Zhang
Keyword(s):  
Real Time ◽  
Emergency Response ◽  
Vertical Direction ◽  
Video Camera ◽  
Measurement Unit ◽  
Wide Angle ◽  
Lidar System ◽  
Multiple Sensors ◽  
Mapping System ◽  
Airborne Mapping

Multisource remote sensing data have been extensively used in disaster and emergency response management. Different types of visual and measured data, such as high-resolution orthoimages, real-time videos, accurate digital elevation models, and three-dimensional landscape maps, can enable producing effective rescue plans and aid the efficient dispatching of rescuers after disasters. Generally, such data are acquired using unmanned aerial vehicles equipped with multiple sensors. For typical application scenarios, efficient and real-time access to data is more important in emergency response cases than in traditional application scenarios. In this study, an efficient emergency response airborne mapping system equipped with multiple sensors was designed. The system comprises groups of wide-angle cameras, a high-definition video camera, an infrared video camera, a LiDAR system, and a global navigation satellite system/inertial measurement unit. The wide-angle cameras had a visual field of 85° × 105°, facilitating the efficient operation of the mapping system. Numerous calibrations were performed on the constructed mapping system. In particular, initial calibration and self-calibration were performed to determine the relative pose between different wide-angle cameras to fuse all the acquired images. The mapping system was then tested in an area with altitudes of 1000 m–1250 m. The biases of the wide-angle cameras were small bias values (0.090 m, −0.018 m, and −0.046 m in the x-, y-, and z-axes, respectively). Moreover, the root-mean-square error (RMSE) along the planer direction was smaller than that along the vertical direction (0.202 and 0.294 m, respectively). The LiDAR system achieved smaller biases (0.117, −0.020, and −0.039 m in the x-, y-, and z-axes, respectively) and a smaller RMSE in the vertical direction (0.192 m) than the wide-angle cameras; however, RMSE of the LiDAR system along the planar direction (0.276 m) was slightly larger. The proposed system shows potential for use in emergency response systems for efficiently acquiring data such as images and point clouds.

Miniature Quadrupole Arrays for Residual and Process Gas Analysis

1999 ◽  
Vol 42 (1) ◽  
pp. 27-31 ◽  
Author(s):  
S. Boumsellek ◽  
R. Ferran
Keyword(s):  
Real Time ◽  
Ray Tracing ◽  
Gas Analysis ◽  
Operating Pressure ◽  
Performance Parameters ◽  
Mass Filter ◽  
Charge Effects ◽  
Multiple Sensors ◽  
Process Gas ◽  
Detection Schemes

This paper includes computer simulations based on ray tracing to aid in the design of miniature quadrupoles. These quadrupoles are then assembled in a matrix-like pattern to operate in parallel. The tradeoffs between sensitivity and resolution for different mechanical and electrical configurations are examined using real-time trajectories of ions. The dependence of resolution versus sensitivity is computed and compared with experimental results. The pressure dependence of the sensitivity is simulated near the upper limit (mtorr range) of the operating pressure. Space charge effects at the inlet of the mass filter are evaluated to properly design electrode apertures and spacing. Using the results of ray tracing, miniature quadrupole arrays were designed and constructed. Performance parameters were derived from recorded spectra and compared with the computations. Since they are able to operate at higher pressures, these sensor-type devices are used as residual gas analyzers (RGAs) and as process gas analyzers (PGAs) in many semiconductor applications. Networking multiple sensors to monitor the state of the semiconductor manufacturing tool and the wafers at different stages of the process enables real-time, wafer-to-wafer control using preset fault detection schemes.

Quantitative mixing rules for downhole oil-based mud contamination monitoring in real time using multiple sensors

2016 ◽  
Vol 137 ◽  
pp. 214-226 ◽  
Author(s):  
Julian Y. Zuo ◽  
Adriaan Gisolf ◽  
Kang Wang ◽  
Francois Dubost ◽  
Thomas Pfeiffer ◽  
...  
Keyword(s):  
Real Time ◽  
Mixing Rules ◽  
Multiple Sensors

scholarly journals Development of Liquid Capacity Measuring Algorithm Based on Data Integration from Multiple Sensors

2016 ◽  
Vol 2016 ◽  
pp. 1-12
Author(s):  
Kiwoong Park ◽  
Si-Kyoung Lee ◽  
Hyeon Cheol Kim
Keyword(s):  
Kalman Filter ◽  
Data Integration ◽  
Real Time ◽  
Rotation Angle ◽  
Sensor Data ◽  
Multiple Sensors ◽  
Complementary Filter ◽  
Level Sensor

This research proposes an algorithm using a process of integrating data from multiple sensors to measure the liquid capacity in real time regardless of the position of the liquid tank. The algorithm for measuring the capacity was created with a complementary filter using a Kalman filter in order to revise the level sensor data and IMU sensor data. The measuring precision of the proposed algorithm was assessed through repetitive experiments by varying the liquid capacity and the rotation angle of the liquid tank. The measurements of the capacity within the liquid tank were precise, even when the liquid tank was rotated. Using the proposed algorithm, one can obtain highly precise measurements, and it is affordable since an existing level sensor is used.

Sign in / Sign up

Export Citation Format

Share Document