Design and Implementation of Real-Time Mobile-based Water Temperature Monitoring System

Bokingkito, Paul B.; Llantos, Orven E.

doi:10.1016/j.procs.2017.12.207

Cited by 32 publications

(15 citation statements)

References 5 publications

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“…This research is different from these works with respect to the multiple platforms and the variety of Linux kernels and distributions upon which it is executed. Several studies show that such Linux-based systems continue to gain more popularity and play an increasing role in the embedded systems real-time control field [63][64][65] and today's Internet of Things applications [66,67]. Nevertheless, there is no sufficient research work in the evaluation of the real-time performance of RPi's and BBAI's Linux kernels patched with PREEMPT_RT.…”

Section: Related Workmentioning

confidence: 99%

Performance Assessment of Linux Kernels with PREEMPT_RT on ARM-Based Embedded Devices

2021

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This work investigates the real-time performance of Linux kernels and distributions with a PREEMPT_RT real-time patch on ARM-based embedded devices. Experimental measurements, which are mainly based on heuristic methods, provide novel insights into Linux real-time performance on ARM-based embedded devices (e.g., BeagleBoard and RaspberryPi). Evaluations of the Linux real-time performance are based on specific real-time software measurement modules, developed for this purpose, and the use of a standard benchmark tool, cyclictest. Software modules were designed upon the introduction of a new response task model, an innovative aspect of this work. Measurements include the latency of response tasks at user and kernel space, the response on the execution of periodic tasks, the maximum sustained frequency and general latency performance metrics. The results show that in such systems the PREEMPT_RT patch provides more improved real-time performance than the default Linux kernels. The latencies and particularly the worst-case latencies are reduced with real-time support, thus making such devices running Linux with PREEMPT_RT more appropriate for use in time-sensitive embedded control systems and applications. Furthermore, the proposed performance measurements approach and evaluation methodology could be applied and deployed on other Linux-based real-time platforms.

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Section: Related Workmentioning

confidence: 99%

Performance Assessment of Linux Kernels with PREEMPT_RT on ARM-Based Embedded Devices

2021

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“…By using plug and play method the device are controlled and data can be transferred with host system. In [6], system were designed in Raspberry pi 3 model B which runs on Linux kernel, DS18B20 digital temperature sensor used to gather the temperature of water which provides 9 to 12 bits temperature readings. In [7], the water meter collects the data about consumption of water at different locations.…”

Section: Related Workmentioning

confidence: 99%

Water Quality Monitoring and Prediction of Water Quality at College Premises using Internet of Things

2019

IJEAT

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IoT is becoming more popular and effective tool for any real time application. It has been involved for various water quality monitoring system to maintain the water hygiene level. The main objective is to build a system that regularly monitors the water quality and manages the sustainability. This system deals with specific standards like low cost background and system efficiency when compared to other studies. In this paper, IoT based real time monitoring of water quality system is implemented along with Machine learning techniques such as J48, Multilayer Perceptron (MLP), and Random Forest. These machine learning techniques are compared based on the hyper-parameters and the results were obtained. The attributes such as pH, Dissolved Oxygen (DO), turbidity, conductivity obtained from the corresponding sensors are used to create a prediction model which classifies the quality of water. Measurement of water quality and reporting system is implemented by using Arduino controller, GSM/GPRS module for gathering data in real time. The collected data are then analyzed using WEKA interface which is a visualization tool used for the analysis of data and prediction modeling.The Random forest technique outperforms J48 and Multilayer perceptron by giving 98.89% of correctly classified instances.

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“…They developed this system basing on an embedded system, logical address and communication application from Internet objects. P. Bokingkito and O. Llantosb [4], were developed a real-time system to monitor water temperature on a mobile that is capable of reducing dependence on the control site workforce to reduce costs and evaluate fish farming system. The implementation of the system led to monitor the water temperature from the main control unit online.…”

Section: Introductionmentioning

confidence: 99%

Water monitoring and analytic based thingspeak

Miry¹,

Aramice²

2020

IJECE

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Diseases associated with bad water have largely reported cases annually leading to deaths, therefore the water quality monitoring become necessary to provide safe water. Traditional monitoring includes manual gathering of samples from different points on the distributed site, and then testing in laboratory. This procedure has proven that it is ineffective because it is laborious, lag time and lacks online results to enhance proactive response to water pollution. Emergence of the Internet of Things (IoT) and step towards the smart life poses the successful using of IoT. This paper presents a water quality monitoring using IoT based ThingSpeak platform that provides analytic tools and visualization using MATLAB programming. The proposed model is used to test water samples using sensor fusion technique such as TDS and Turbidity, and then uploading data online to ThingSpeak platform to monitor and analyze. The system notifies authorities when there are water quality parameters out of a predefined set of normal values. A warning will be notified to user by IFTTT protocol.

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Design and Implementation of Real-Time Mobile-based Water Temperature Monitoring System

Cited by 32 publications

References 5 publications

Performance Assessment of Linux Kernels with PREEMPT_RT on ARM-Based Embedded Devices

Performance Assessment of Linux Kernels with PREEMPT_RT on ARM-Based Embedded Devices

Water Quality Monitoring and Prediction of Water Quality at College Premises using Internet of Things

Water monitoring and analytic based thingspeak

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