REAL-TIME ANORMALY DETECTION OF RIVER WATER LEVEL OBSERVATION BASED ON PROBABILITY DISTRIBUTION OF WATER LEVEL ESTIMATION ERROR

2019 ◽  
Vol 75 (2) ◽  
pp. I_193-I_198
Author(s):  
Masayuki HITOKOTO ◽  
Noriko KAWAGOE ◽  
Hajime HASHIDA ◽  
Yuichi SEI ◽  
Kazutomo FUSAMAE
Keyword(s):  
Probability Distribution ◽  
Water Level ◽  
Real Time ◽  
River Water ◽  
Estimation Error

scholarly journals Automated Alert System for River Water Level and Water Quality Assessment using Telegram Bot API

2021 ◽  
Vol 6 (3) ◽  
pp. 65-74
Author(s):  
Iman Hazwam Abd Halim ◽  
Ammar Ibrahim Mahamad ◽  
Mohd Faris Mohd Fuzi
Keyword(s):  
Water Quality ◽  
Water Level ◽  
Real Time ◽  
River Water ◽  
Monitoring System ◽  
Ph Sensor ◽  
Ultrasonic Sensor ◽  
Water Levels ◽  
Water Monitoring ◽  
The Internet

Technology has advanced to the point that it can assist people in their daily lives. Human beings may benefit from this development in a variety of ways. Progress in river water monitoring is also one of them. There are many advantages in improving the river water monitoring system. The objective of this project is to develop an automated system for monitoring river water levels and quality with push notification features. Internet of Things (IoT) was implemented in this research by using NodeMCU as a microcontroller to connect both ultrasonic sensors and pH sensors to the Internet. An ultrasonic sensor is used to read the water level, and a pH sensor is used to read the water pH values. The results show the successful output from all of 10 time attempts to obtain more accurate test results. The results will be averaged to be analysed and concluded from the test. All the tests include testing for the accuracy of the ultrasonic sensor, the accuracy of the pH sensor, and the performance of the internet connection using integrated Wi-Fi module in NodeMCU microcontroller. The system test also shows that it performs perfectly with the requirement needed to send the real-time status of the water level, water quality and an alert to the user using the Telegram Bot API. This research can help to increase the level of awareness of the river water monitoring system. This research was done by looking at people's problems in the vicinity of the river area by producing a system tool that helps to monitor the river water in real-time status.

scholarly journals Short Term Real-Time Rolling Forecast of Urban River Water Levels Based on LSTM: A Case Study in Fuzhou City, China

2021 ◽  
Vol 18 (17) ◽  
pp. 9287
Author(s):  
Yu Liu ◽  
Hao Wang ◽  
Wenwen Feng ◽  
Haocheng Huang
Keyword(s):  
Water Level ◽  
Real Time ◽  
River Water ◽  
Urban Areas ◽  
Urban River ◽  
Water Levels ◽  
Urban Water ◽  
Short Term ◽  
Forecast Performance ◽  
Flood Season

Water level management is an important part of urban water system management. In flood season, the river should be controlled to ensure the ecological and landscape water level. In non-flood season, the water level should be lowered to ensure smooth drainage. In urban areas, the response of the river water level to rainfall and artificial regulation is relatively rapid and strong. Therefore, building a mathematical model to forecast the short-term trend of urban river water levels can provide a scientific basis for decision makers and is of great significance for the management of urban water systems. With a focus on the high uncertainty of urban river water level prediction, a real-time rolling forecast method for the short-term water levels of urban internal rivers and external rivers was constructed, based on long short-term memory (LSTM). Fuzhou City, China was used as the research area, and the forecast performance of LSTM was analyzed. The results confirm the feasibility of LSTM in real-time rolling forecasting of water levels. The absolute errors at different times in each forecast were compared, and the various characteristics and causes of the errors in the forecast process were analyzed. The forecast performance of LSTM under different rolling intervals and different forecast periods was compared, and the recommended values are provided as a reference for the construction of local operational forecast systems.

AUTOMATIC WATER LEVEL MONITORING WITH IOT AND LPWAN

2019 ◽  
pp. 95-103
Author(s):  
Krum Videnov ◽  
Vanya Stoykova
Keyword(s):  
Water Level ◽  
Real Time ◽  
Early Warning ◽  
Water Sources ◽  
Water Levels ◽  
Water Level Fluctuations ◽  
Level Monitoring ◽  
Water Level Monitoring

Monitoring water levels of lakes, streams, rivers and other water basins is of essential importance and is a popular measurement for a number of different industries and organisations. Remote water level monitoring helps to provide an early warning feature by sending advance alerts when the water level is increased (reaches a certain threshold). The purpose of this report is to present an affordable solution for measuring water levels in water sources using IoT and LPWAN. The assembled system enables recording of water level fluctuations in real time and storing the collected data on a remote database through LoRaWAN for further processing and analysis.

Network Selection in Wireless Heterogeneous Environment Based on Available Bandwidth Estimation

2019 ◽  
Vol 12 ◽  
Author(s):  
Kiran Ahuja ◽  
Brahmjit Singh ◽  
Rajesh Khanna
Keyword(s):  
Real Time ◽  
Estimation Error ◽  
Network Selection ◽  
Bandwidth Estimation ◽  
Heterogeneous Environment ◽  
Bootstrap Approximation ◽  
Available Bandwidth ◽  
Internet Connection ◽  
Available Bandwidth Estimation ◽  
Selection Of

Background: With the availability of multiple options in wireless network simultaneously, Always Best Connected (ABC) requires dynamic selection of the best network and access technologies. Objective: In this paper, a novel dynamic access network selection algorithm based on the real time is proposed. The available bandwidth (ABW) of each network is required to be estimated to solve the network selection problem. Method: Proposed algorithm estimates available bandwidth by taking averages, peaks, low points and bootstrap approximation for network selection. It monitors real-time internet connection and resolves the selection issue in internet connection. The proposed algorithm is capable of adapting to prevailing network conditions in heterogeneous environment of 2G, 3G and WLAN networks without user intervention. It is implemented in temporal and spatial domains to check its robustness. Estimation error, overhead, estimation time with the varying size of traffic and reliability are used as the performance metrics. Results: Through numerical results, it is shown that the proposed algorithm’s ABW estimation based on bootstrap approximation gives improved performance in terms of estimation error (less than 20%), overhead (varies from 0.03% to 83%) and reliability (approx. 99%) with respect to existing techniques. Conclusion: Our proposed methodology of network selection criterion estimates the available bandwidth by taking averages, peaks, and low points and bootstrap approximation method (standard deviation) for the selection of network in the wireless heterogeneous environment. It monitors real-time internet connection and resolves internet connections selection issue. All the real-time usage and test results demonstrate the productivity and adequacy of available bandwidth estimation with bootstrap approximation as a practical solution for consistent correspondence among heterogeneous wireless networks by precise network selection for multimedia services.

River Water Level Prediction in Coastal Catchment using hybridized relevance vector machine model with improved grasshopper optimization

2021 ◽  
pp. 126477
Author(s):  
Hai Tao ◽  
Najah Kadhim Al-Bedyry ◽  
Khaled Mohamed Khedher ◽  
Shamsuddin Shahid ◽  
Zaher Mundher Yaseen
Keyword(s):  
Water Level ◽  
River Water ◽  
Relevance Vector Machine ◽  
Machine Model ◽  
Grasshopper Optimization ◽  
Water Level Prediction

Research on the Distributed Characteristics of the Delay for Network Coding Based Real-Time Multicast in MANETs

2014 ◽  
Vol 530-531 ◽  
pp. 768-772
Author(s):  
Guo Ping Tan ◽  
Lin Feng Tan ◽  
Lei Cao ◽  
Mei Yan Ju
Keyword(s):  
Maximum Likelihood ◽  
Probability Distribution ◽  
Network Coding ◽  
Real Time ◽  
Lognormal Distribution ◽  
Ad Hoc ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Actual Distribution ◽  
Delay Distribution

For the study of the applications of partial network coding based real-time multicast protocol (PNCRM) in Mobile Ad hoc networks, the researches should be developed in the probability distribution of delay. In this paper, NS2 is used to obtain the delay of data packets through simulations. Because the delay does not obey the strict normal distribution, the maximum likelihood estimate method based on the lognormal distribution is used to process the data. Using MATLAB to obtain the actual distribution of the natural logarithm of delay, then drawing the delay distribution with the maximum likelihood estimation method based on the lognormal distribution, the conclusion that the distributions obtained by the above mentioned methods are basically consistent can be obtained. So the delay distribution of PNCRM meets the lognormal distribution and the characteristic of delay probability distribution can be estimated.

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