Academic literature on the topic 'Private weather station'
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Journal articles on the topic "Private weather station"
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Dombrowski, Olga, Harrie-Jan Hendricks Franssen, Cosimo Brogi, and Heye Reemt Bogena. "Performance of the ATMOS41 All-in-One Weather Station for Weather Monitoring." Sensors 21, no. 3 (January 22, 2021): 741. http://dx.doi.org/10.3390/s21030741.
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Affordable and accurate weather monitoring systems are essential in low-income and developing countries and, more recently, are needed in small-scale research such as precision agriculture and urban climate studies. A variety of low-cost solutions are available on the market, but the use of non-standard technologies raises concerns for data quality. Research-grade all-in-one weather stations could present a reliable, cost effective solution while being robust and easy to use. This study evaluates the performance of the commercially available ATMOS41 all-in-one weather station. Three stations were deployed next to a high-performance reference station over a three-month period. The ATMOS41 stations showed good performance compared to the reference, and close agreement among the three stations for most standard weather variables. However, measured atmospheric pressure showed uncertainties >0.6 hPa and solar radiation was underestimated by 3%, which could be corrected with a locally obtained linear regression function. Furthermore, precipitation measurements showed considerable variability, with observed differences of ±7.5% compared to the reference gauge, which suggests relatively high susceptibility to wind-induced errors. Overall, the station is well suited for private user applications such as farming, while the use in research should consider the limitations of the station, especially regarding precise precipitation measurements.
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Bolongho, Ruwan. "Microcontroller based Multifunctional Automated Weather Monitoring and Logging System." International Journal for Research in Applied Science and Engineering Technology 9, no. 11 (November 30, 2021): 189–98. http://dx.doi.org/10.22214/ijraset.2021.38773.
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Abstract: This paper describes a microcontroller-based prototype Automated Weather Monitoring and Logging System that can col- lect meteorological data such as air temperature, relative humidity, atmospheric pressure, light intensity, and rain detection from any distant location. The Weather Monitoring and Logging System is entirely automated, and measured weather data is transferred to a public server while showing immediate data on a liquid crystal display (LCD) and stored to a Secure Digital (SD) card. For private viewers, Android-based smart phones may be interfaced with the weather station and operated via the android application. The weather station is supplied by a direct current (DC) source, with a backup rechargeable battery. In the event of an emergency power outage, the system will immediately switch to battery power. Two Atmega 328p and Two ESP 8266 microcontrollers are utilized as the core of the control and coordination of the relative multitude of exercises of the singular modules. All of the sensors in the systems have been calibrated, ensuring that the system’s accuracy seems to be exceptional. This system will benefit all users, and it will benefit the meteorological industry because it will allow them to work from a remote location. Keywords: Automated Weather Station; Microcontroller; Sensor; Meteorological Instrument
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Mutz, Sebastian G., Samuel Scherrer, Ilze Muceniece, and Todd A. Ehlers. "Twenty-first century regional temperature response in Chile based on empirical-statistical downscaling." Climate Dynamics 56, no. 9-10 (January 23, 2021): 2881–94. http://dx.doi.org/10.1007/s00382-020-05620-9.
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AbstractLocal scale estimates of temperature change in the twenty-first century are necessary for informed decision making in both the public and private sector. In order to generate such estimates for Chile, weather station data of the Dirección Meteorológica de Chile are used to identify large-scale predictors for local-scale temperature changes and construct individual empirical-statistical models for each station. The geographical coverage of weather stations ranges from Arica in the North to Punta Arenas in the South. Each model is trained in a cross-validated stepwise linear multiple regression procedure based on (24) weather station records and predictor time series derived from ERA-Interim reanalysis data. The time period 1979–2000 is used for training, while independent data from 2001 to 2015 serves as a basis for assessing model performance. The resulting transfer functions for each station are then directly coupled to MPI-ESM simulations for future climate change under emission scenarios RCP2.6, RCP4.5 and RCP 8.5 to estimate the local temperature response until 2100 A.D. Our investigation into predictors for local scale temperature changes support established knowledge of the main drivers of Chilean climate, i.e. a strong influence of the El Niño Southern Oscillation in northern Chile and frontal system-governed climate in central and southern Chile. Temperature downscaling yields high prediction skill scores (ca. 0.8), with highest scores for the mid-latitudes. When forced with MPI-ESM simulations, the statistical models predict local temperature deviations from the 1979–2015 mean that range between − 0.5–2 K, 0.5–3 K and 2–7 K for RCP2.6, RCP4.5 and RCP8.5 respectively.
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Onofre, Thiago Borba, Clyde W. Fraisse, Janise McNair, Jasmeet Judge,, Lincoln Zotarelli, and Natalia A. Peres. "Development of a Wireless Sensor Network for Field Level Strawberry Disease Alert Systems." Applied Engineering in Agriculture 37, no. 1 (2021): 183–92. http://dx.doi.org/10.13031/aea.13738.
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HighlightsFungal diseases are considered a major challenge for strawberry farmers.Disease risk monitoring systems can be improved with increased spatial coverage of environmental conditions.Wireless Sensor Networks (WSN) with customized nodes can efficiently collect site-specific data inputs for disease risk models.WSN providing disease risk levels with increased spatial and temporal resolution opens the opportunity for site-specific control actions.Abstract. The United States is the world’s largest producer of strawberries, harvesting over 680 million metric tons in 2017, valued at approximately $3.2 billion. Fungal diseases are considered a major challenge for strawberry farmers. Even in well-managed fields, losses from fungal diseases can exceed 50% when environmental conditions favor disease development. Anthracnose fruit rot (AFR), caused by Colletotrichum acutatum and Botrytis fruit rot (BFR), caused by Botrytis cinerea, are the most significant diseases monitored (or present) during strawberry production in Central Florida and worldwide. The Strawberry Advisory System (SAS) was developed by researchers at the University of Florida to alert strawberry growers of infection risk of AFR and BFR. SAS also recommends control actions when necessary. In Florida, the SAS uses leaf wetness duration and temperature observed at Florida Automated Weather Network (FAWN) stations and private weather stations to estimate strawberry disease risk. A good representation of local conditions is crucial, but unfortunately uncommon in modern fungal disease warning systems (FDWS), such as the SAS. In this study, we developed and deployed an in-field Wireless Sensor Network (WSN) with customized nodes (WetBerry). WetBerry is a distributed mesh network of wireless mini weather stations equipped with leaf wetness, temperature, and relative humidity sensors developed to monitor in-field environmental conditions related to the risk of fungal diseases in strawberry production. The WSN mini weather stations were installed and tested in a strawberry field during the 2017/2018 strawberry season, and the results were validated against a standard agrometeorological weather station. The WSN provided high spatial and temporal density of weather data for agricultural applications, thereby has the potential to improve the capabilities of site-specific fungal disease warning tools and control actions. Keywords: Decision making, Fungal disease, Leaf wetness, Precision agriculture, Site-specific, WSN.
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Werg, Jana Lorena, Torsten Grothmann, Michael Spies, and Harald A. Mieg. "Factors for Self-Protective Behavior against Extreme Weather Events in the Philippines." Sustainability 12, no. 15 (July 27, 2020): 6010. http://dx.doi.org/10.3390/su12156010.
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We report the results on factors for self-protective behavior against weather extremes such as extreme heat events, drought, and heavy precipitation. Our research draws on the Model of Private Proactive Adaptation to Climate Change (MPPACC). We developed a survey instrument incorporating the main aspects of the MPPACC and other factors from related research work that are assumed to explain why some people show self-protective behavior while others do not. The interview survey was conducted with a non-random sample of 210 respondents from three Philippine cities, namely Baguio, Dagupan, and Tuguegarao. The results reveal the importance of adaptation appraisal, including the perceived feasibility of self-protective measures, the perceived adaptation knowledge, and, with limitations, the perception of actions taken by neighbors or friends. We also show that perceptions of past weather trends are closely linked to risk perception but are only partly corroborated by weather station data. Implications for fostering self-protective behavior are making use of time windows right after an extreme weather event and focusing on enhancing adaptation appraisal.
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Danilovich, Margaret, Aura Espinoza, and Christie Norrick. "Weather, Built Environment, or Personal Factors: Predictors of Walking by Independent Living Residents With Frailty." Innovation in Aging 5, Supplement_1 (December 1, 2021): 447–48. http://dx.doi.org/10.1093/geroni/igab046.1734.
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Abstract Environmental factors influence older adult physical activity. However, the evidence about which factors lead to increased physical activity is mixed and few have studied how these factors affect those with frailty or living in retirement communities. This study investigated how environmental and weather factors influence physical activity among pre-frail and frail older adults residing in independent living retirement communities. We used ActivPal accelerometers to measure 7-day step counts among (n=108) pre-frail and frail residents in 9 independent living residences in metropolitan Chicago. We conducted environmental audits using the MAPS Abbreviated tool and collected National Weather Service Station data (temperature, precipitation, and daylight minutes) during the ActivPal periods. Participants were on average 80.0 years, 74% female, and average daily step count was 3,450 (range 151 - 11,663). Four buildings were in suburban areas and 5 in urban areas and four were private-pay residences while 5 offered subsidized rent. ANOVA results showed private-pay buildings had higher total MAPS scores than subsidized buildings (p=0.001), and urban buildings had higher total MAPS scores than suburban buildings (p < 0.000). Mean step differences were non-significant between different building types: (mean steps = 3,317 private-pay, 3,629 subsidized, 3,536 urban, 3,350 suburban). Pearson product-moment correlations showed a positive association between steps and MAPS positive streetscape features (p=0.011). Multiple regression analysis showed higher temperature days, precipitation, and more minutes of daylight were associated with higher step counts (p=.04). Given the dramatic variation in individual step counts, future research should investigate personal factors that contribute to activity among independent living residents.
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Alomari, Mohammad H., Jehad Adeeb, and Ola Younis. "Solar Photovoltaic Power Forecasting in Jordan using Artificial Neural Networks." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 1 (February 1, 2018): 497. http://dx.doi.org/10.11591/ijece.v8i1.pp497-504.
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In this paper, Artificial Neural Networks (ANNs) are used to study the correlations between solar irradiance and solar photovoltaic (PV) output power which can be used for the development of a real-time prediction model to predict the next day produced power. Solar irradiance records were measured by ASU weather station located on the campus of Applied Science Private University (ASU), Amman, Jordan and the solar PV power outputs were extracted from the installed 264KWp power plant at the university. Intensive training experiments were carried out on 19249 records of data to find the optimum NN configurations and the testing results show excellent overall performance in the prediction of next 24 hours output power in KW reaching a Root Mean Square Error (RMSE) value of 0.0721. This research shows that machine learning algorithms hold some promise for the prediction of power production based on various weather conditions and measures which help in the management of energy flows and the optimisation of integrating PV plants into power systems.
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Alomari, Mohammad H., Jehad Adeeb, and Ola Younis. "PVPF tool: an automatedWeb application for real-time photovoltaic power forecasting." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 1 (February 1, 2019): 34. http://dx.doi.org/10.11591/ijece.v9i1.pp34-41.
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<p>In this paper, we propose a fully automated machine learning based forecasting system, called Photovoltaic Power Forecasting (PVPF) tool, that applies optimised neural networks algorithms to real-time weather data to provide 24 hours ahead forecasts for the power production of solar photovoltaic systems installed within the same region. This system imports the real-time temperature and global solar irradiance records from the ASU weather station and associates these records with the available solar PV production measurements to provide the proper inputs for the pre-trained machine learning system along with the records’ time with respect to the current year. The machine learning system was pre-trained and optimised based on the Bayesian Regularization (BR) algorithm, as described in our previous research, and used to predict the solar power PV production for the next 24 hours using weather data of the last five consecutive days. Hourly predictions are provided as a power/time curve and published in real-time at the website of the renewable energy center (REC) of Applied Science Private University (ASU). It is believed that the forecasts provided by the PVPF tool can be helpful for energy management and control systems and will be used widely for the future research activities at REC.</p>
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Marquès, Eva, Valéry Masson, Philippe Naveau, Olivier Mestre, Vincent Dubreuil, and Yves Richard. "Urban Heat Island Estimation from Crowdsensing Thermometers Embedded in Personal Cars." Bulletin of the American Meteorological Society 103, no. 4 (April 2022): E1098—E1113. http://dx.doi.org/10.1175/bams-d-21-0174.1.
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Abstract An ever-growing portion of the global population lives in urban areas. Cities are expanding quickly and consequently, the urban heat island effect has become a major health concern to maintain city dwellers’ thermal comfort. For this reason, city planners want to access urban meteorological databases in local areas where specific attention is needed. With the growth of connected devices, it is possible to collect unusual but massive temperature measurements from people’s activities. In this article, we study temperatures measured by thermometers embedded in everyday personal cars. To assess the quality of such opportunistic data, we first detect factors deteriorating the measurement. After preprocessing, the measurement error is then estimated thanks to two weather station networks providing a local-scale reference through the cities of Dijon and Rennes, France. The overall aggregation of private car temperature measurements allows us to estimate very precisely the urban heat island at a 200-m resolution. We detect the cooling effect of parks in Rennes and Paris urban areas. In Barcelona and Dijon, we observe the impact of regional environments and the orographic effect on the urban heat island. With our method, similar maps can be made accessible to every interested city in western Europe to target critical areas and support urban planning decisions.
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Hartin, Janet S., David W. Fujino, Lorence R. Oki, S. Karrie Reid, Charles A. Ingels, and Darren Haver. "Water Requirements of Landscape Plants Studies Conducted by the University of California Researchers." HortTechnology 28, no. 4 (August 2018): 422–26. http://dx.doi.org/10.21273/horttech04037-18.
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University of California (UC) researchers have been involved in research and extension pertaining to measuring evapotranspiration (ET) rates and determining the minimum irrigation requirements of landscape plants for more than 30 years. Early work included the design and implementation of the California Irrigation Management Information System (CIMIS) weather station network and determining crop coefficients for warm and cool season turfgrasses based on historical ET and CIMIS data. Other researchers determined the minimum irrigation requirements for several species of established landscape trees, shrubs, and groundcovers in diverse climate zones throughout the state. In addition, the Water Use Classification of Landscape Species (WUCOLS) system was developed by UC personnel in the early 1990s which, to date, has classified more than 3500 landscape species into very low, low, moderate, and high water-use categories based on observation and personal experience by industry experts and UC personnel. Future work in the area of landscape water use and conservation will include updating WUCOLS as more data from replicated trials become available. New research at UC Riverside aims to improve irrigation efficiency (IE) through precision irrigation using smart controllers, remote sensing, and geospatial analysis under controlled conditions. Irrigation training and certification for public and private landscape managers must remain a priority because, even with advanced smart controller technologies, water savings will not occur with poorly designed and functioning irrigation systems.
Dissertations / Theses on the topic "Private weather station"
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Хижняк, Олександр Сергійович. "Система аналізу даних приватної метеорологічної станції." Bachelor's thesis, КПІ ім. Ігоря Сікорського, 2020. https://ela.kpi.ua/handle/123456789/40931.
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Пояснювальна записка дипломного проєкту містить 6 розділів, 61 сторінка, 35 рисунків, 7 таблиць, посилання на 18 літературних джерела, додатки та 4 кресленики.
Об’єктом розробки: система аналізу даних для приватна метеостанція.
Мета розробки: створити застосунок зі зручним інтерфейсом, який буде аналізувати погодні показники минулих днів та годин.
У дипломному проєкті розроблено систему, яка в режимі реального часу збирає дані погодних показників, аналізує їх та виводить користувачу у вигляді тексту або у вигляді графіків за останні дні або 12 годин. Проведено ретельний огляд існуючих рішень і на основі цього виконано аналіз вимог, які б задовольняли всім потребам як звичайного користувача, так і садівника-любителя або ж працівника на господарстві. За апаратну частину було обрано мікроконтролер ESP8266 та датчики DHT22 і BMP280 для вимірювання температури, вологості повітря, атмосферного тиску та теплового індексу. Значну увагу було приділено серверній частині, яка розгортається в хмарному ресурсі Microsoft Azure.
Отримані результати можуть бути розширені масштабованістю апаратної частини та подальшою розробкою функціональної системи. Будуть корисними як звичайній, так і зацікавленій в господарстві людині.The explanatory note of the diploma project consists of 6 sections, 61 pages, 35 figures, 7 tables, links to 18 literary sources, annexes and 4 design documents. The object of the development: the data analysis system for private weather station. The purpose of the development: create an application with user friendly interface for analyzing weather data of the last days and hours. The graduation project developed the system, which collects weather data in real time, analyzes it and displays results like text or like charts for the last days or 12 hours. The thorough analysis of existing solutions and applications is a base of requirements that will satisfy all simple people, amateur gardener’s or enterprise worker’s needs. Microcontroller ESP8266 and sensors DHT22 and BMP280 were chosen like an embedded part of system for temperature, humidity, atmosphere pressure and heat index measurements. Considerable attention was paid to the server part, which is deployed in the cloud platform Microsoft Azure. The results obtained can be expanded by scalability of embedded part and functional system future development. It will useful as for simple people as for interested in the enterprise person.
Books on the topic "Private weather station"
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Observing Weather And Climate From The Ground Up A Nationwide Network Of Networks. National Academies Press, 2009.
Find full textBook chapters on the topic "Private weather station"
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Kirstein, Fabian, Dario Bacher, Vincent Bohlen, and Sonja Schimmler. "Ronda: Real-Time Data Provision, Processing and Publication for Open Data." In Lecture Notes in Computer Science, 165–77. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-84789-0_12.
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AbstractThe provision and dissemination of Open Data is a flourishing concept, which is highly recognized and established in the government and public administrations domains. Typically, the actual data is served as static file downloads, such as CSV or PDF, and the established software solutions for Open Data are mostly designed to manage this kind of data. However, the rising popularity of the Internet of things and smart devices in the public and private domain leads to an increase of available real-time data, like public transportation schedules, weather forecasts, or power grid data. Such timely and extensive data cannot be used to its full potential when published in a static, file-based fashion. Therefore, we designed and developed Ronda - an open source platform for gathering, processing and publishing real-time Open Data based on industry-proven and established big data and data processing tools. Our solution easily enables Open Data publishers to provide real-time interfaces for heterogeneous data sources, fostering more sophisticated and advanced Open Data use cases. We have evaluated our work through a practical application in a production environment.
Conference papers on the topic "Private weather station"
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Quiniou-Ramus, Valérie, Rémi Estival, Pascal Venzac, and Jean-Baptiste Cohuet. "Real-Time Network of Weather and Ocean Stations: Public-Private Partnership on In-Situ Measurements in the Gulf of Guinea." In ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/omae2013-10903.
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Monitoring of meteorological or/and oceanographic conditions is done on many Oil & Gas platforms offshore West and Central Africa (from Nigeria to Angola), but it is often only used in real-time and not necessarily archived on a hard-drive, or it is protected by each company’s IT firewalls thus making it difficult to send the information to the “outer world”. In 2010, TOTAL Oil & Gas Operator launched a project to give remote and public access to this real-time wind, current and also wave or other meteorological / oceanographic (“metocean”) data. The objectives of this initiative were multiple: • Improve weather and ocean hindcasts and forecasts, which will be beneficial to all Oil & Gas operations in Africa, • Help feed a database for future O&G developments; • Enable design checks after ∼1 year of operation; • Serve as a “black box” in case of an incident which could be due to environment; • Help feed or validate ocean and oil spill drift forecast in case of emergency; • Contribute to the international effort of monitoring the oceans in the long term (operational oceanography, climate change, etc.); • Encourage capacity building in Africa by supporting development and maintenance of technical solutions to reach objectives In 2013, with the support of the French Meteorological Office Météo-France, the data from half a dozen platforms offshore Nigeria, Congo and Angola will be available on the World Meteorological Organization’s (WMO) Global Telecommunication System (GTS). This paper will present the type of metocean stations that are part of this network “MODANET”, the IT architecture that was selected to send it out of the Company’s network, the quality control undertaken by Meteo France before sending it to the GTS, and future possible use of the data that are envisaged.