Monitoring Of Environmental Parameters Research Articles

Salient features of West Bengal coastal ecosystem and effective management of environment

The thickly populated coastal region of West Bengal has a unique combination of valuable mineral resources blanketed by mainly medium to fine grained sands, silts and clays and is the focal area for rapid development of societal structure. A number of multi mineral placer deposits existing in the Bakkhali, Sagar and Digha coastal belt of West Bengal are being used up rapidly. There is an urgent need for exploration of mineral resources in these areas. Economic heavy minerals in this coastal area include ilmenite, rutile, magnetite, leucoxene, zircon, monazite, sillimanite and garnet. All these resources are renewable and attention should be given to explore and exploit these deposits which are often available in large quantity. A tremendous resource crunch is inevitable due to constant exploitation of land based resources and thus there is an urgent need to look for resources in the coastal zone and offshore areas. Important processes are energy flows, sunlight, water flow, recycling, temperature, dissolved gas, presence of chemicals, availability of nutrients. The salinity, water condition and visual appearance of the basin is also important. Attention should be paid to develop indigenous technology for exploration and development. The cost effectiveness of tapping the resources should be kept in mind, Monitoring of environmental parameters viz. air, water, soil, noise, vibration, flora, fauna is essential. Analyses and preservation of biodiversity is necessary. The administrative area for management must be a coupled unit of coastal water basins and adjacent shorelines. The objectives of a Coastal Zone Management Programme for the state should be kept in mind to develop a national policy and legislation and ensure integrated approaches to assess and evaluate a sustainable development policy, some of the local and special management plans should be carefully developed. The impact of socioeconomic environment considering the financial, technological and features in decision making should improve the proper planning. Resource utilization, coastal planning and management are critical issues. The existing and projected impacts for future must help the government to enforce decisions based on environmental impact assessmentand improve proper planning.

AUTOMATED SYSTEM FOR BEE COLONY WEIGHT MONITORING

Real time, continuous and remote monitoring of the honeybee colonies with application of information and communication technologies (ICT) is becoming increasingly frequent in industry and in a scientific research. Combination of ICT and beekeeping led to the development of the Precision Beekeeping approach. Successful implementation of the Precision Beekeeping system includes development of the bee colony monitoring hardware solution and computer software for data collection and further analysis. This paper describes developed and implemented bee colony monitoring unit for weight and temperature monitoring. Bee colony weight is one of the key metrics of the strength of a colony. Changes in weight can reflect the productivity rate of the colony, as well as its health and state. Developed monitoring system is based on Raspberry Pi Zero W single board computer with several connected sensors for bee colony temperature and environmental parameter monitoring. Weight is measured using single point load cell with possibility to measure weight up to 200kg, which is enough for the beehive measurements. Data transfer from the remote bee colony is provided by the external 3G router. For data storage and analysis cloud-based data warehouse is developed. Collected data is accessible in the web system with user friendly interface for data visualisation and reporting. Within this research scale calibration process is described and accuracy of the weighting is evaluated and possible challenges are discussed. Described monitoring system is developed within the Horizon 2020 project SAMS, which is funded by the European Union within the H2020-ICT-39-2016-2017 call. To find out more visit the project website https://sams-project.eu/.

Development of a system for monitoring environmental parameters of cities and open areas

This article is devoted to the development of a system for monitoring the state of the ecological environment. The system under development should provide ongoing monitoring of environmental air parameters, both in open areas and in the city, and is designed to timely detect excess concentrations of hazardous substances in the air. A distinctive feature of the created system is high productivity at low economic costs per accounting point. An appropriate selection of the component base and software optimization of the operation algorithms will allow to achieve the maximum data transmission distance over a distance of up to 100 km in an open area. Interim results on the development of a monitoring system are presented, planned tasks for this year are indicated.

Data Acquisition of Multiple Sensors in Greenhouse Using Arduino Platform

Continuous monitoring of environmental parameters is necessary in order to achieve maximum plant growth in a greenhouse system. The aim of this study is to perform a real time data monitoring from multiple sensors in greenhouse using Arduino and Excel add-ins. DHT22 sensors, BH1750 sensor are the main sensors used in this study which give the exact value of temperature, humidity, and light intensity, respectively. Arduino Uno board provides multiple inputs analogs and I/O digitals were utilized to read the data sensor aforementioned that applied for the greenhouse. The level of accuracy of each sensor was compare to the standard device results. The results show that the accuracy of the sensors measurement is very good. This system design is real time, simple and low cost that given ability for user to monitor, collect, and to plot their greenhouse environments data in an Excel sheet.

Crop Management in Controlled Environment Agriculture (CEA) Systems Using Predictive Mathematical Models.

Proximal sensors in controlled environment agriculture (CEA) are used to monitor plant growth, yield, and water consumption with non-destructive technologies. Rapid and continuous monitoring of environmental and crop parameters may be used to develop mathematical models to predict crop response to microclimatic changes. Here, we applied the energy cascade model (MEC) on green- and red-leaf butterhead lettuce (Lactuca sativa L. var. capitata). We tooled up the model to describe the changing leaf functional efficiency during the growing period. We validated the model on an independent dataset with two different vapor pressure deficit (VPD) levels, corresponding to nominal (low VPD) and off-nominal (high VPD) conditions. Under low VPD, the modified model accurately predicted the transpiration rate (RMSE = 0.10 Lm−2), edible biomass (RMSE = 6.87 g m−2), net-photosynthesis (rBIAS = 34%), and stomatal conductance (rBIAS = 39%). Under high VPD, the model overestimated photosynthesis and stomatal conductance (rBIAS = 76–68%). This inconsistency is likely due to the empirical nature of the original model, which was designed for nominal conditions. Here, applications of the modified model are discussed, and possible improvements are suggested based on plant morpho-physiological changes occurring in sub-optimal scenarios.

A secure authentication framework for WSN-based safety monitoring in coal mines

Underground coal mines are considered as one of the most dangerous workspaces as many hazardous factors regularly cause accidents. It may be avoided by real-time monitoring of environmental parameters (gas, temperature, the width of walls, etc.) of underground tunnels. Nowadays, wireless sensor network (WSN) is widely used for safety monitoring of coal mines. However, any kind of interception, modification and interruption of transmission of environmental parameters can mislead the professionals that might lead to a major accident. Therefore, security is an essential issue for WSN-based safety monitoring. Sensors in WSN have limited computational power and storage capacity, which creates a challenge to design authentication and key agreement (AKA) scheme with low computational cost. To address these issues, As this scheme is light-weight and provides mutual authentication (MA), sensor anonymity (SA) and user anonymity (UA), we have considered this scheme for a case study. We first propose the cryptanalysis of this scheme, in which we prove that this scheme fails to resist sensor node compromise (SNC), stolen smart card (SSC) and user impersonation (UI) attacks. To counteract these attacks and to provide efficient authentication scheme, we propose a lightweight AKA scheme for WSN-based safety monitoring in coal mines. We simulated the scheme on AVISPA tool. We used the random oracle model (ROM) to perform formal security analysis and also performed informal security analysis. These analyses demonstrate that the proposed scheme is secure and invulnerable to various known attacks. We compared the proposed scheme to other related schemes regarding security features and computational cost. Our scheme requires comparable computational cost and is more secure than related schemes.

Physiological and Behavior Monitoring Systems for Smart Healthcare Environments: A Review.

Healthcare optimization has become increasingly important in the current era, where numerous challenges are posed by population ageing phenomena and the demand for higher quality of the healthcare services. The implementation of Internet of Things (IoT) in the healthcare ecosystem has been one of the best solutions to address these challenges and therefore to prevent and diagnose possible health impairments in people. The remote monitoring of environmental parameters and how they can cause or mediate any disease, and the monitoring of human daily activities and physiological parameters are among the vast applications of IoT in healthcare, which has brought extensive attention of academia and industry. Assisted and smart tailored environments are possible with the implementation of such technologies that bring personal healthcare to any individual, while living in their preferred environments. In this paper we address several requirements for the development of such environments, namely the deployment of physiological signs monitoring systems, daily activity recognition techniques, as well as indoor air quality monitoring solutions. The machine learning methods that are most used in the literature for activity recognition and body motion analysis are also referred. Furthermore, the importance of physical and cognitive training of the elderly population through the implementation of exergames and immersive environments is also addressed.

Chemometrics modelling of temporal changes of ozone half hourly concentrations in different monitoring stations

Principal Component Analysis and Multivariate Curve Resolution (MCR) chemometrics soft modelling approaches are proposed for the simultaneous analysis of the half hourly tropospheric ozone concentrations over a continuous period of six years at three different monitoring stations. The proposed approach is based on the direct multilinear modelling of experimental data without needing any prior physicochemical, geographical nor meteorological assumptions. By application of the proposed modelling approach, a summarized description of the changes of ozone concentrations due to a reduced number of contributions is achieved. Each one of these contributions is described by a set of diurnal, seasonal, year and location profiles whose interpretation is then possible using the available knowledge. The use of the proposed chemometrics approach can be generalized for the analysis and interpretation of environmental big data sets generated in continuous on-line monitoring of multiple environmental parameters over long time periods and for a large number of monitoring stations.

Fog Harvesting and IoT based Environment Monitoring System at the Ilalo volcano in Ecuador

Environmental monitoring is critical to develop appropriate policies for environmental sustainability. The quality of drinking and agricultural water is affected by bad environmental management strategies. In addition, natural water sources have been reduced due to climate changes and the lack of police and compliance with regulations for water resources management. In the Andes region of Ecuador, these problems have increased in recent decades. The lack of water affects not only human well-being, but also causes soil degradation. Therefore, finding alternative water sources has become the underlying requirement to provide human well-being and mitigate soil degradation in these regions. This article presents a fog collection system based on water condensation towers and Internet of Things (IoT) technology with real-time monitoring. Our system allows monitoring of environmental parameters while providing alternative sources of water from the environmental fog. Therefore, by collecting information related to the process of fog collection and climatic measurements of the environment, we seek to determine the state and trends of environmental conditions with respect to the performance of fog collection. In addition, our system allows the storage of historical environmental data, which can be used to develop environmental management policies. We have deployed our system on the slopes of the Ilalo volcano, Pichincha province, being part of the Ecuadorian Andes, where the soil deterioration has increased in recent years and has the largest soil degradation rate in Ecuador

Zigbee-based wireless gas monitoring sensor alarm system in coal mine

In view of the underground monitoring and monitoring system of coal mine, wired data transmission has been used in the past, but there are some disadvantages such as complicated wiring work, large amount of labor, fixed network structure which is not convenient to meet the dynamic requirements and low stability. Therefore, this study designs a monitoring system based on ZigBee wireless sensor network, wireless transmission, strong mobility, high reliability, low power consumption, strong real-time performance, etc, can be real-time monitoring of the coal mine environment parameters, including downhole temperature, humidity and gas concentration, and the acquisition of information sent by ZigBee wireless transmission way. STM32F103RBT6 is adopted as the wireless network processor in the system, which is responsible for establishing the network and transmitting data. NDIR HC sjh-5 CUBIC gas concentration sensor to collect underground mine data; Wireless SZOS embedded wireless communication module is used as the wireless sending and receiving port to enhance the wireless sending power. The software architecture adopts ZigBee protocol stack. The research shows that the proposed ZigBee wireless sensor network based coal mine underground gas monitoring system can help improve the real-time monitoring level and reduce safety risks in the complex and special environment of coal mine underground.

Study of the variations in the Schumann resonances parameters measured in a southern Mediterranean environment.

Schumann resonances (SRs) provide a unique tool for exploring continuous and long-term monitoring of global environmental parameters, although their detection and study is a very complex task. This paper presents diurnal and seasonal variations of principal parameters, namely the resonance frequency, the Q-factor, and the power of SRs, in the North-South (NS) magnetic field component for the first five modes from Extra Low Frequency (ELF) measurements. These were acquired at the observation site located at Doliana, Kalpaki, in the Region of Epirus, North West Greece. These variations are the first ones reported for the principal parameters in the South Eastern Mediterranean area and correspond to the one-year measurement period from 2016 to 2017. The comparison with variations at several observations sites is also discussed. Moreover, correlation with global lighting centers, as well as local lightning activity, and SRs parameters variation is attempted.

Monitoring of Environmental Parameters and Automatic Control of Irrigation System

Agriculture is the root to countries economic development. In this project I have tried to focus on the better growth of the plant or crop. For the better growth of the crop, humidity is the main factor. Due to the less humidity, it contributes to problems such as root diseases, loss of quality, less production of crop. In that time the farmer needs to use the more chemicals for the better growth. So, to reduce such problems I tried the project which depends on the humidity level and soil temperature. By providing sufficient water to plant we can prevent the problems such as root diseases. Then we can obtain natural products. This circuit contains three sensors they are Light intensity sensor, humidity sensor, soil temperature sensor. Humidity sensor measures both the temperature and humidity, soil temperature sensor measures the temperature in the soil it displays the values on LCD through the Microcontroller (Arduino board). These three sensors are input sensors. Arduino board is used to output the result by dumping the program. This board displays the result on LCD display. In this project the motor gets ON when the soil temperature is less than the required value in the soil of a crop field. The motor gets OFF when the humidity is reached to required level. Additionally it also displays some environmental parameters such as soil temperature, ambient temperature and Light intensity around the plant in a crop. The values will be displayed on the LCD display and also we can observe the graphs for all these parameters by using Thing Speak the cloud platform.

Determination of the main parameters of the photovoltaic solar module

This article deals with the determination of the main operating parameters of a photovoltaic solar module. In laboratory tests, the study of the dependence of current, voltage and power on time and density of solar radiation, as well as monitoring of environmental parameters: temperature and humidity of the outside air. Analysis of the test results shows that a photoelectric module with an installed capacity of 800 W and a total battery capacity of 800 Ah provides the electric power industry with a daily consumption of 2.0 ... 2.2 kWh. The discharge time of the battery varies from 11.7 to 3.5 hours when the average electric load of the consumer changes from 300 to 1000 watts.

A low cost solution to monitor environmental parameters in industrial area perimeters

The monitoring of environmental parameters in active industrial areas where there exist potential sources of pollution, and even more so in the area of decommissioned or closure mining activities, is very important from the point of view of prevention of environmental accidents. In this paper, we propose a solution for the monitoring of the environmental parameters with the local acquisition and processing of the data and the transmission of alarm signals to a higher hierarchical level through the use of radio communications. A flexible hardware structure and software development concept are presented to be integrated into the national air quality monitoring network.

Smart IOT System for Monitoring and Controlling Livestock Parameters

In this paper we consider the products like quality and welfare of animals which are closely related to the environment parameters in livestock building. A monitoring and control method of environmental parameters in livestock buildings based on wireless sensor network is proposed in this system. The parameters like temperature, humidity, light intensity, carbon dioxide concentration, ammonia concentration, and hydrogen sulfide concentration can be monitored and controlled in real time by this method. These parameters can be adjusted and controlled through WLS algorithm and also can minimize the deviation criteria. Along with this, the system can also track the location of the animals in the livestock building using several tracking nodes placed around the neck of the animal. In addition, the system proposes the ALEXA based voice assistant which is a user friendly system that can assist us to control and monitor the livestock parameters. Compared with the traditional method, the proposed method reduces the high labour cost and energy consumption will be decreased.

Prospects and opportunities for the introduction of digital technologies into aquaculture governance system

It is possible to increase the efficiency of pond farms by introducing new digital technologies into the technological processes of fish cultivation. Recirculating aquaculture systems serve a positive example of high technology applications in aquaculture. Automated control of all processes in pond fish farming starting from pond preparation for stocking of fish to placement and production of commercial fish will significantly increase the efficiency of fish farming by 70-80% thus increasing the overall profit by 20-30%. For properly organized feeding of fish it is necessary to take into account many factors, such as: fish-holding density, temperature of water and air, content of oxygen dissolved in water, ph-level of water and feed intake. The system of complex automation of any production enterprise shall be implemented taking into account the technologies of the fourth industrial revolution – Industry 4.0. The main unit of the system is an automated floating feeder with autonomous power supply from solar panels. The design and functional features of the feeder will determine the functionality of the entire automation system: automatic feeding, monitoring of water and environmental parameters, deoxidation of the water basin, supplementary feeding with insects, frightening of fish-eating birds. The innovative approach proposed by the authors is that if the pond is equipped with several floating feeders it is necessary to connect them to each other in a single information system, which functions through wireless radio communication. The assessment of the potential of the proposed modernization of a middle pond made it possible to increase the profit by 1.5 million rubles.

Information Integration and Environmental Monitoring for Cage Pigeons

Environmental changes in the farm can have a significant impact on the healthy growth of cage pigeons, disease prevention and the quality of pigeon meat. The stability and adaptability testing of environmental monitoring equipment and systems was completed through the pilot deployment of IoT Ranch in a pigeon farm in Beijing. An integrated program for real-time monitoring of environmental parameters of cage pigeons is implemented. Moreover, a system for informatizing and researching environmental information and real-time querying information on a webpage or mobile terminal is developed. The information-integrated environmental monitoring equipment and system can provide technical support for the modernization, automation and digital management of cage pigeons.

Assessing energy saving potentials of office buildings based on adaptive thermal comfort using a tracking-based method

Occupants’ thermal comfort and their adaptation behaviors are essential aspects of building design and energy operation. There is a growing need to better understand the impact of seasonal variation on occupants’ dynamic thermal comfort which provides evidence for building energy flexible design and management. The aim of this study is to investigate the interaction between occupants’ thermal sensation and adaptive behavior in office buildings. Such understanding can provide detailed adaptation rules of human behavior in dynamic office buildings and quantify energy demands. In this study, a framework of a tracking method is proposed, which combines data collection (continuous monitoring of environmental parameters and daily questionnaire surveys), time boundary division and data analysis. Using the tracking method, field surveys were carried out in three mixed-mode office buildings in Chongqing, China. The time-series data was analyzed based on the indoor operative temperature under free-running conditions and five seasonal periods are classified i.e. Latter Spring (LS), Early Cooling period (EC), Middle Cooling period (MC), Latter Cooling period (LC) and Early Autumn (EA). Results show that for the same outdoor temperatures in different seasons, occupants’ clothing insulation varied, indicating that the occupants were more sensitive to environmental changes in EA than in LS, as well as in EC than in LC. The study that flexible energy operation based on the thermal comfort demand can achieve energy savings compared with fixed temperature.

Integrating qualitative and quantitative research to develop the final archetypes: Developing home occupant archetypes: First results of mixed-methods study to understand occupant comfort behaviours and energy use in homes

To better understand home energy consumption, it is important to study the behaviours of occupants in their homes, especially in relation to their comfort needs. A mixed methods study comprising of a questionnaire, interviews, indoor environmental parameters monitoring, and energy consumption readings was performed to group home occupants based on their behavioural patterns. The TwoStep cluster analysis produced five clusters of home occupant with the data from 761 questionnaire respondents. The clustering model comprised of 28 variables including constructs of emotions, comfort affordances, and locus of control. Then, in-depth semi-structured interviews were conducted and IEQ monitoring and energy readings were taken with 15 of the questionnaire respondents. The results of the field study were used to substantiate the findings of the questionnaire. The combination of the statistical clusters with the data from the field study resulted in five archetypes: five distinct types of home occupants, differing in their behavioural motivations towards achieving comfort, and their use of energy when doing so. This study shows that a mixed methods approach is valuable for better understanding energy consumption and implementing archetype-customized lines of action to reduce energy use and maintain comfort.

Outlier Detection in Wireless Sensor Networks Data by Entropy Based K-NN Predictor

Anomaly (outlier) detection is plays very significant role in ESN based monitoring application using on large data used for biomedical and defence. Wireless Sensor network monitor environmental parameters (temperature, humidity, pressure, vibration etc). Group of sensor nodes forms a (WSN) and observations collected from these sensor produces low data quality and reliability due to the limited energy, memory, computation capability and bandwidth. The dynamic environment of network and roughness of the working condition are also responsible to generate inaccuracy in measurements. In this paper, an approach for outliers detection based entropy value of received sensor voltages is applied using KNN prediction model .The algorithm development and analysis involves a real time database generated on 14 sets of MICA2 wireless sensor kit with anomaly inserted by real time motion based intrusion in the lab by volunteers from Intel Berkeley lab. On each sensor data pair segmentation is applied by fixed window size in order get large outliers’ measurements training dataset. The analysis demonstrates the measurement accuracy in detection of number of outliers that its 86%. Moreover, the algorithm also provides an analysis in terms of impact of variation in distance types and number of nearest neighbours in the KNN prediction model. This work is helpful in the application in the situations where high amount of noise or distortions are present. The outlier part from distorted data can be figured out and recollected to enhance application accuracy.