Parameter Monitoring System Research Articles

Design of Health Detection System for Elderly Smart Watch Based on Biosignal Acquisition

The health monitoring of the elderly has attracted increasing attention of researchers. Based on the biosignal acquisition method, this paper proposes a design structure of the health detection system for smart watches for the elderly and realizes the effective detection of health signals by analyzing the Lipschitz exponent of the maximum value column of the transform. The multiphysiological parameter acquisition and monitoring system of the wearable smart watch designed in this paper can continuously monitor the physiological parameters of the elderly such as body temperature, pulse, and respiration for a long time and solve the problem of the accuracy of the health detection of the elderly. In the simulation process, based on the performance of the synchronization source and the difference of the network path, the model applies the multivariate and multiscale biological signals to collect the human gait acceleration. The experimental results show that, compared with the international recognition rate obtained for this data set, the highest recognition rate obtained by the method in this paper reaches 96.5%, which can provide a calibration accuracy of 1 ~ 50 ms, and the synchronized system time and the national time service center network are given. The error obtained by comparing the published time is within 50 ms, which meets the accuracy requirements of the time protocol. The results fully prove that the algorithm in this paper can effectively extract the biosignal features of the elderly’s health detection and has good statistical features and classification accuracy.

Rancang Bangun Sistem Monitoring dan Uji Analisis Performansi Tranformator berbasis Internet of Things (IoT)

Maintenance on transformers is currently carried out on a monthly basis, which activities are carried out manually so that it is difficult to detect transformers experiencing abnormal conditions if there is a disturbance outside the maintenance schedule. Therefore, this research was carried out with the aim of making a prototype of a transformer condition monitoring system and monitoring parameters on the transformer remotely through the Blynk application in real time. In making this tool, the PZEM-004T sensor is used to read electrical parameters, the DS18B20 sensor to read the temperature on the transformer winding and the Arduino MEGA 2560 With WiFi Built-in - ESP8266 to process the data read by the sensor which is then sent to the Blynk application. The results of this study indicate that the average error value for the comparison of current readings is 0.68%, the average error value for the comparison between phase to neutral voltage readings is 0.91%, the average error value for the comparison of voltage readings between phases is 1, 00%, the average error value of the Cosφ reading comparison is 0.02% and the average temperature reading comparison error value is 1.73%.

Purwarupa Sistem Pemantauan dan Pengendalian Pertumbuhan Tanaman Cabai dalam Screen House

Chili (Capsicum annuum L.) is a well-known spice plant and is loved because of its distinctive spicy taste. In addition, chili also contains good nutrients including vitamins A, B, C, E, potassium, phosphorus, calcium, folate, antioxidants, protein, and anti-cancer substances. Chili cultivation provides good economic potential because market demand is stable and even increases in certain seasons. One of the chili planting methods is by using a screen house which allows farmers to better control various growth parameters. In this study, an IoT-based monitoring and control system for chili plant growth parameters was developed using a Raspberry Pi, sensors, and other electronic devices. Growth parameter data is processed and sent to an online server and then presented with a time series-based visualization.

Anti-Theft System for Two Wheelers

This project presents a smart bike with monitoring system for cyclist via internet of things (IoT). The system is designed for real time monitoring of cyclist in terms of health condition and cyclist's performance. The whole system consists of various sensors such as heart rate sensor, pulse oximetry sensor, magnet reed sensor and GPS module. The sensors are connected to the microcontroller and Wi-Fi module that can be accessed through an IoT platform which is blink application. The data of the cyclist in terms of health condition and cyclist's performance can be monitored by the cyclist as well as their coach. First, heart rate sensor was used to monitor the heart rate of the cyclist within time whereas pulse oximetry sensor was used to measure the oxygen saturation inside the cyclist's body. Meanwhile, magnet reed sensor was mounted to the frame of the bike to measure the speed and distance travelled by the cyclist. Plus, GPS module was used to track and trace the position of the cyclist. The data that have been transmitted can be synchronized or displayed on smartphone via blink application. Therefore, GUI interface of blink application displayed the parameter such as heart rate, pulse oximetry, speed, distance travelled and position for the cyclist and coach to monitor their health condition and cyclist's while in training or tournament. IoT is the internetworking of physical devices, vehicles, and other devices embedded with the electronics, software, sensors and network connectivity that enable to get data of those objects. Confiscating details from their own vehicle without making any physical touch is a hardly possible one. Augmentation of Smartphone makes a large impact in society by diminishing their toil. A surge movement of applications in the Smartphone may cutback the human’s accent. In India transportation is a booming field where the count of vehicles increasing day by day. Security and maintenance of those vehicles is a risky one. Monitoring vehicle parameters like fuel, engine oil, tyre pressure is an ideal to know without making any physical touch of the vehicle. Digital locking system is a much needed one in this digital domain. Tracking of our vehicle is also a vital one when your vehicle is not with you. IoT based vehicle parameter monitoring system is a capable one which leads to monitor our vehicle’s parameters such as fuel level, tyre pressure, engine oil level through an Android App. It’s Smart RFID digital key secure your vehicle more than by accessing by keys. In this app we can save our vehicle documents, user driving license, insurance copy and other documents. Notification for engine oil, battery rejuvenation is also done. Message and share’s location to trusted persons whenever ensue accidents..

Development of a Low-cost Arduino-based Patient Monitoring System for Heartrate, Oxygen Saturation and Body Temperature Parameters

The implementation of Patient Monitor (PM) in ICU, ICCU, PICU and NICU currently imposes a significantly high cost of investment. According to studies conducted, there are three main parameters required to be measured, which are heartrate (BPM), oxygen saturation (SPO2) and body temperature (T). These are highly needed by the medical personnel to monitor in order to determine patient’s vital state. The low-cost patient monitor prototype (named Patient Monitor 3 Parameters or PM3P) was developed using Arduino platform. In order to measure the parameters, two types of sensor modules were chosen, namely MAX30100 for gathering heartrate and oxygen saturation data and DS18B20 for gathering the body temperature data. The prototyping process also included fixation and finalization of electrical circuit on a printed circuit board (PCB). The PM3P underwent extensive validation process by comparing it to the real industrial PM made by healthcare equipment industry. The comparison was done over data gathered by both system that were conducting the same measurement runs in parallel. Results of validation indicates that the low-cost patient monitor prototype has a slight error of 0,31% for heartrate and 1,59% for oxygen saturation compared to the industrial one. Further improvements for the Arduino based PM3P are also proposed in this paper in order to enhance its reading accuracy, namely calibration.

Design and Implementation of Electrical Parameter Monitoring System Based on ZigBee Wireless Communication

In order to solve the problems of many lines, troublesome movement and redundant management of traditional electrical parameter monitoring system, a design and implementation of electrical parameter monitoring system based on ZigBee wireless communication is proposed. Taking the monitor as an example, this paper briefly introduces the application status of the monitor monitoring system and electrical safety detection. According to the comparison of wireless communication technology and the analysis of actual demand, this paper expounds the advantages of ZigBee wireless technology. Based on the combination of received signal strength indication (RSSI) ranging algorithm and trilateral positioning algorithm, the wireless positioning of mobile targets is realized. Then, the sparse correlation matrix of signal attenuation coefficient between base stations is established in the upper computer to optimize the positioning by using the look-up table method. The relevant test results show that through the serial port test software 2000 times of data transmission and reception, 1866 times of communication are successful, and the success rate is 93.3%, which basically meets the requirements of data transmission stability; After data transmission time detection, it takes about 1.4 seconds to send data from the monitor to the client for reception. The client sends the module query command, and the time when the command reaches the monitor is 1.6 seconds. The data transmission speed can basically meet the requirements of real-time monitoring. The design and implementation of the monitoring system can not only help to reduce the workload of medical staff in hospital nurse stations and improve their work efficiency, but also provide the possibility of practical significance for developing into an application tool for patient family members or personal health management in the future.

Information model of heat stress effect on lactation performance of cows

The article considers the outcomes of national and foreign research on the heat stress effect on the milking ability of cows. The previously designed monitoring system of inside climate parameters was used to obtain the experimental data and to create an information model of the effect of temperature and humidity conditions in the barn on the milk productivity of animals. The model allows us to monitor the physiological state of lactating cows and following the weather forecast to take the advance organizational and technological measures to provide comfortable conditions for the animals.

“Remote Health Monitoring of elder using Wearable Sensor.”

Abstract: Wearable physiological monitoring devices are used to monitor the health status of a Patient in Intensive Care Units (ICU). These systems are wired everywhere. A wireless Physiological parameter monitoring system is presented in this paper. Literature review carried out in the area of wearable physiological monitoring systems. The proposed system includes sensors for continuous collection and evaluation of physiological parameters. A wireless personal area network has been introduced for reliable transmission of physiological information. The hardware design of this patient monitoring system is based on 8051 microcontrollers. Microcontroller acts as the gateway to ZigBee and GSM module. ZigBee wireless communication module has the advantage of lower power consumption which is attractive for portable applications. This system provides safe and accurate monitoring. It also gives the freedom of movement. The proposed system can be used to monitor the physiological condition of a person in out of hospitalcondition also. Keywords: Pulse Sensor, Temperature Sensor, ZigBee,Microcontroller, LCD, Buzzer Arduino.

IoT Technologies in Chemical Analysis Systems: Application to Potassium Monitoring in Water.

The in-line determination of chemical parameters in water is of capital importance for environmental reasons. It must be carried out frequently and at a multitude of points; thus, the ideal method is to utilize automated monitoring systems, which use sensors based on many transducers, such as Ion Selective Electrodes (ISE). These devices have multiple advantages, but their management via traditional methods (i.e., manual sampling and measurements) is rather complex. Wireless Sensor Networks have been used in these environments, but there is no standard way to take advantage of the benefits of new Internet of Things (IoT) environments. To deal with this, an IoT-based generic architecture for chemical parameter monitoring systems is proposed and applied to the development of an intelligent potassium sensing system, and this is described in detail in this paper. This sensing system provides fast and simple deployment, interference rejection, increased reliability, and easy application development. Therefore, in this paper, we propose a method that takes advantage of Cloud services by applying them to the development of a potassium smart sensing system, which is integrated into an IoT environment for use in water monitoring applications. The results obtained are in good agreement (correlation coefficient = 0.9942) with those of reference methods.

Perancangan Sistem Monitoring Parameter Kualitas Udara (Suhu, CO, LPG dan Debu) berbasis IOT

Research has been carried out on the design of a monitoring system for air quality parameters (temperature, CO, LPG and dust) whose data is integrated in real time. The measuring instrument uses the Arduino Uno R3 microcontroller base. The MQ-9 and MQ-5 gas sensors are used to measure air pollution, while the LM35 and DSM 501A sensors are used for temperature and dust. This system is also connected with Xbee S2 as a data sender and receiver based on WIFI. The voltage source is connected to a 10 W solar panel which is regulated by the charger controller so that when the battery is full, the battery charging connection will be disconnected. The software used is Arduino IDE 1.8.1 and X-CTU. The data that can be measured by the tool is the level of air pollution of CO and LPG gas, air temperature and PM 2.5 particulates in the air. The measurement phase was tested with samples of gas (CO and LPG) as well as a heat source and a cold source for temperature. The test data shows that all sensors are able to detect the presence of CO and LPG gas, temperature differences and dust levels in the air and then display the data in real time.

Design of Wind Turbine Parameter Monitoring and Early Warning Software System Based on Deep Learning Modeling

This paper adopts deep learning self-encoding algorithm, using JAVA, C++ and python language mixed programming computing technology to realize wind turbine parameter monitoring and early warning and software system design and development. This paper describes the database design, process management mode, fault early warning model, alarm value processing and human-computer interaction interface of the system, explains the software operation process and workflow, as well as the early warning mechanism and algorithm of the system, and realizes the early fault early warning function of wind turbine operation parameters.

Design and Analysis of Industrial Automation using Speech Recognition with Wireless Technology

Today, Internet is the best place to communicate and share information among the people throughout the world and gives an endless support of knowledge and entertainment. The main objective of Internet technology is to increase efficiency and decrease human effort. With the introduction of Internet of Things (IoT) in the last decade, we have been pushing for ubiquitous computing in all spheres of life. Physically challenged people are also using the Internet with the help of Speech commands (SC). The main objective of this paper is to minimize the effort and increase efficiency of the Voice recognition and IoT based secured automation, To design multi parameter monitoring system using Microcontroller that measures and controls various global parameters and the system comprises with wireless mode of communication. These processes were managed using Arduino and Bluetooth. The parameters that can be tracked are temperature, humidity and fire. Here we design the automatic system for voice based industrial automated system. That is an android app is used to give input data as voice input to the micro controller. In the micro controller section there will be a Bluetooth module to receive the data transmitted. Once the data is received the coding is executed according to the data which the controller got. Here we can monitor the temperature, humidity and gas and fire value of the industry and according to the values the prevention action is taken. The motor, dc fan and the light is turned on and off according to the voice input. And the action done here is implemented to the IOT.

Internet of things-based photovoltaics parameter monitoring system using NodeMCU ESP8266

<span>The use of the internet of things (IoT) in solar photovoltaic (PV) systems is a critical feature for remote monitoring, supervising, and performance evaluation. Furthermore, it improves the long-term viability, consistency, efficiency, and system maintenance of energy production. However, previous researchers' proposed PV monitoring systems are relatively complex and expensive. Furthermore, the existing systems do not have any backup data, which means that the acquired data could be lost if the network connection fails. This paper presents a simple and low-cost IoT-based PV parameter monitoring system, with additional backup data stored on a microSD card. A NodeMCU ESP8266 development board is chosen as the main controller because it is a system-on-chip (SOC) microcontroller with integrated Wi-Fi and low-power support, all in one chip to reduce the cost of the proposed system. The solar irradiance, ambient temperature, PV output voltage and PV output current, are measured with photo-diodes, DHT22, impedance dividers and ACS712. While, the PV output power is a product of the PV voltage and PV current. ThingSpeak, an open-source software, is used as a cloud database and data monitoring tool in the form of interactive graphics. The results showed that the system was designed to be highly accurate, reliable, simple to use, and low-cost.</span>

A multiple Linear Regression Model to predict indoor temperature trend in historic buildings for book conservation: the case study of “Sala del Dottorato” in Palazzo Murena, Italy

The indoor climate of historic buildings is governed by the desire to preserve them, their interiors and to ensure human comfort. For preservation of cultural heritage and libraries, relative humidity and temperature are very important parameters, including their amplitudes and changes rate in time. In the present study an experimental campaign of thermo-hygrometric parameters inside of “Sala del Dottorato”, located in Palazzo Murena (Perugia), is carried out. In this room a great number of rare and ancient books are preserved. The paper deals with the study and the evaluation of the correlation between outdoor and indoor microclimate conditions in the room, to ensure the proper conservation of the books; it is aimed at understanding how the two parameters follow outdoor variations and how the hygrothermal inertia of the building can mitigate these variations. This is done, specifically for temperature, which is the most critical aspect. Thanks to a continuous monitoring system for indoor and outdoor thermo-hygrometric parameters, a Multiple Linear Regression model is developed in order to predict and analyse the indoor temperature trend. This model allows to estimate a future forecast of this parameter and to predict in advance critical conditions for correct conservation.

Real-Time Monitoring and Static Data Analysis to Assess Energetic and Environmental Performances in the Wastewater Sector: A Case Study

Real-time monitoring of energetic-environmental parameters in wastewater treatment plants enables big-data analysis for a true representation of the operating condition of a system, being still frequently mismanaged through policies based on the analysis of static data (energy billing, periodic chemical–physical analysis of wastewater). Here we discuss the results of monitoring activities based on both offline (“static”) data on the main process variables, and on-line (“dynamic”) data collected through a monitoring system for energetic-environmental parameters (dissolved oxygen, wastewater pH and temperature, TSS intake and output). Static-data analysis relied on a description model that employed statistical normalization techniques (KPIs, operational indicators). Dynamic data were statistically processed to explore possible correlations between energetic-environmental parameters, establishing comparisons with static data. Overall, the system efficiently fulfilled its functions, although it was undersized compared to the organic and hydraulic load it received. From the dynamic-data analysis, no correlation emerged between energy usage of the facility and dissolved oxygen content of the wastewater, whereas the TSS removal efficiency determined through static measurements was found to be underestimated. Finally, using probes allowed to characterize the pattern of pH and temperature values of the wastewater, which represent valuable physiological data for innovative and sustainable resource recovery technologies involving microorganisms.

Smart water grid: a review and a suggestion for water quality monitoring

Abstract Water is a valuable resource and an elixir of life. It is intimately linked to living standards around the world. Reducing water stress and conserving the resource is vital. It is the need of the hour to ameliorate conventional water resources systems to monitor water quantity and quality parameters continuously in real-time. Smart solutions play an important role in monitoring system parameters and making on-site measurements. This paper focuses on Smart Water Grid, an ingenious way to monitor and preserve the quantity and quality parameters in real-time by deploying remote sensors in the water distribution system. It presents a review of various sensors deployed, networking protocols used and cloud platforms employed in monitoring the water distribution system. The suitable networking protocols for the water distribution systems are suggested by analyzing various smart solutions. It also proposes an architecture for an IoT-based system to monitor residual chlorine concentration in the water distribution system. Smart Water Grid using Wireless Sensor Networks and the Internet of Things enables the monitoring of on-site conditions and generates alerts during abnormal conditions. It can enhance timely decision-making which will help in managing valuable water resources more efficiently.

Precision seeding parameter monitoring system based on laser sensor and wireless serial port communication

With the development of agricultural intelligence, the degree of integration of computer technology, wireless communication technology, sensor technology, and agricultural machinery technology is getting higher and higher. Among them, the seeding parameter monitoring technology of the seeder has been more and more applied. However, the current seeding monitoring technology still has some problems, including the low accuracy of parameter monitoring, the monitoring parameters are mainly the seeding quantity, the data is communicated by wire connection, the communication distance is short, the wiring is complicated, and the scalability is poor. Aiming at the problems existing in the current seeding parameter monitoring technology, this study designed and developed a precision seeding parameter monitoring system based on laser sensors and wireless serial port communication for precision seeders. The monitoring system included the design of laser sensor, the design of controller parameter capture and calculation, the design of upper computer human–computer interaction software, the design of wireless communication methods, the design of fault alarm, and speed measurement function. Bench tests had shown that the monitoring system designed in this study had high monitoring accuracy. When the simulated seeder was at a forward speed of 5–10 km/h, the average monitoring error of the seeding quantity was less than 1.2%, and the average monitoring error of the seeding qualified rate was less than 0.5%. The monitoring system could accurately and timely alarm the fault, which the success rate of alarm reached 100%, and the average response time of the fault alarm was less than 0.5 s. The GPS speed measurement value was consistent with the simulation software value, and the speed measurement frequency was 5 Hz. Field tests had shown that the average monitoring error of the seeding quantity was less than 1%, and the average monitoring error of the seeding qualified rate was less than 1.5%. The monitoring system could alarm in time when the seeder had a missing seeds fault. Through test verification, the monitoring system designed in this study could realize the online real-time monitoring function of the precision seeder.

Research on Design, Detection and Realization of Monitoring System Based on Ship Power Grid Parameter

The power system of the ship is closely related to the it’s shipping, production and operation, navigation and communication, daily life and other subsystems, and has a very important impact on the operation of the ship. Due to the characteristics of the micro-grid of the ship and the use of a large number of power electronic equipment, the reliability of the power system of the ship is reduced, and the power quality of the power grid continues to decline. This paper studies the power parameter monitoring of the ship’s power grid, and designs a power parameter monitoring system for the ship’s power grid, which can monitor the power parameters of the ship’s power grid in real time. It is helpful to master the operation of the ship power system, and plays a positive role in improving the power quality of the ship power grid, and ensuring the safety and economic operation of the ship power system.

Study of IoT Based Smart Water Quality Monitoring System

IoT based water quality parameter monitoring system is a significant interest in the field of cost-effective smart water quality monitoring systems. As we know that the population growth of your country is high in last few decades. In India, the demand for freshwater for drinking purposes, agriculture, and other activities is much higher than compared to other countries. The requirement of a smart water quality parameter monitoring system is necessary to reduce the time required in the traditional approach of water quality monitoring, and for real time monitoring. This literature survey work has been conducted in the field of smart water quality parameter monitoring systems. Sensor-based smart water quality parameter monitoring in past some research carried out which is deployed in the water.

Using Machine Learning for Dependable Outlier Detection in Environmental Monitoring Systems

Sensor platforms used in environmental monitoring applications are often subject to harsh environmental conditions while monitoring complex phenomena. Therefore, designing dependable monitoring systems is challenging given the external disturbances affecting sensor measurements. Even the apparently simple task of outlier detection in sensor data becomes a hard problem, amplified by the difficulty in distinguishing true data errors due to sensor faults from deviations due to natural phenomenon, which look like data errors. Existing solutions for runtime outlier detection typically assume that the physical processes can be accurately modeled, or that outliers consist in large deviations that are easily detected and filtered by appropriate thresholds. Other solutions assume that it is possible to deploy multiple sensors providing redundant data to support voting-based techniques. In this article, we propose a new methodology for dependable runtime detection of outliers in environmental monitoring systems, aiming to increase data quality by treating them. We propose the use of machine learning techniques to model each sensor behavior, exploiting the existence of correlated data provided by other related sensors. Using these models, along with knowledge of processed past measurements, it is possible to obtain accurate estimations of the observed environment parameters and build failure detectors that use these estimations. When a failure is detected, these estimations also allow one to correct the erroneous measurements and hence improve the overall data quality. Our methodology not only allows one to distinguish truly abnormal measurements from deviations due to complex natural phenomena, but also allows the quantification of each measurement quality, which is relevant from a dependability perspective. We apply the methodology to real datasets from a complex aquatic monitoring system, measuring temperature and salinity parameters, through which we illustrate the process for building the machine learning prediction models using a technique based on Artificial Neural Networks, denoted ANNODE ( ANN Outlier Detection ). From this application, we also observe the effectiveness of our ANNODE approach for accurate outlier detection in harsh environments. Then we validate these positive results by comparing ANNODE with state-of-the-art solutions for outlier detection. The results show that ANNODE improves existing solutions regarding accuracy of outlier detection.