Peningkatan Skalabilitas Mini Weather Station Portable berbasis Internet of Things

Indonesia is a country that has unique weather that provides not only abundant natural resources but also can causes disasters at any time. To reduce the threat of losses, observing weather elements using a weather station is a solution that can be used. The development of systems related to environmental monitoring and weather stations is not new. However, most research focuses on various innovations in utilization, low cost and power savings. These studies have not touched on the aspect of ease of system development, especially in the concept of adding nodes. Indonesia, as a country with diverse regional topography, needs an integrated weather monitoring system with the concept of centralized data collection to get a complete picture.In this study, a portable mini weather station system was built named Amicagama. This system is built with the concept of high scalability which means the system is designed to be used publicly, with each user able to manage the nodes which are their respective weather stations. Management by each user here means that each user can manage weather data to be submitted, add nodes at a new location, and can delete nodes at a certain location if something unexpected happens.

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Development of a Low-Cost Arduino-Based Weather Station

FUOYE Journal of Engineering and Technology ◽

10.46792/fuoyejet.v5i2.508 ◽

2020 ◽

Vol 5 (2) ◽

Author(s):

Temilola M Adepoju ◽

Matthias O Oladele ◽

Abdulwakil A Kasali ◽

Gbenga J Fabiyi

Keyword(s):

Data Collection ◽

Data Storage ◽

Low Cost ◽

Data Communication ◽

Weather Data ◽

Weather Station ◽

Atmospheric Conditions ◽

Rf Transceiver ◽

Temperature And Humidity ◽

Arduino Uno

A weather station is a facility located either on land or sea consisting of instruments and equipment which can be used to measure atmospheric conditions so as to provide weather forecasts information and to study the weather. The existing instruments used for measuring the weather elements are expensive which led to the development of a low-cost Arduino-based weather station. The developed low-cost weather station consists of three separate modules which are data collection, data storage, and data communication. These modules communicate serially with each other and are controlled by three separate microcontrollers (Arduino Uno). The data collection module is interfaced with a set of sensors that collects temperature and humidity. The weather data were viewed in real-time through a graphical user interface (GUI) located at the central station. The developed weather station was able to measure the temperature and humidity of a controlled environment, giving the reading at interval of five minutes. It was observed that the average temperature from results obtained (27.360C) with the developed low-cost Arduino based weather station falls within the range of the Accuweather readings (24.00-28.000C). Also, the average humidity of the developed low-cost Arduino based weather station (80.41%) falls within the range of the Weatherspark humidity (78-82%) on 20th August 2019. Therefore, this system can be adopted as a weather station facility. The design can be extended to be web-based in the future to make it available worldwide.Keywords— Arduino Uno, Humidity, RF Transceiver, Temperature, Weather Station

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Design and Implementation of an Energy-Efficient Weather Station for Wind Data Collection

Sensors ◽

10.3390/s21113831 ◽

2021 ◽

Vol 21 (11) ◽

pp. 3831

Author(s):

Padma Balaji Leelavinodhan ◽

Massimo Vecchio ◽

Fabio Antonelli ◽

Andrea Maestrini ◽

Davide Brunelli

Keyword(s):

Data Collection ◽

Precision Agriculture ◽

Climatic Factors ◽

Wind Data ◽

Weather Data ◽

Weather Station ◽

Weather Patterns ◽

Weather Stations ◽

Iot Devices ◽

Local Weather

Agriculture faces critical challenges caused by changing climatic factors and weather patterns with random distribution. This has increased the need for accurate local weather predictions and weather data collection to support precision agriculture. The demand for uninterrupted weather stations is overwhelming, and the Internet of Things (IoT) has the potential to address this demand. One major challenge of energy constraint in remotely deployed IoT devices can be resolved using weather stations that are energy neutral. This paper focuses on optimizing the energy consumption of a weather station by optimizing the data collected and sent from the sensor deployed in remote locations. An asynchronous optimization algorithm for wind data collection has been successfully developed, using the development lifecyle specifically designed for weather stations and focused on achieving energy neutrality. The developed IoT weather station was deployed in the field, and it has the potential to reduce the power consumption of the weather station by more than 60%.

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A Multidimensional Internet of Things Testbed System: Development and Evaluation

Wireless Communications and Mobile Computing ◽

10.1155/2020/8849433 ◽

2020 ◽

Vol 2020 ◽

pp. 1-17

Author(s):

Ibrahim S. Alsukayti

Keyword(s):

Internet Of Things ◽

Technology Acceptance ◽

Positive Impact ◽

System Development ◽

Low Cost ◽

Evaluation Study ◽

General Purpose ◽

Study Results ◽

Software Modules ◽

Acceptance Model

The technological breakthrough of the Internet of Things (IoT) drives the emergence of a wide scope of smart IoT solutions in different domains. Advancing the different technological aspects of these solutions requires effective IoT implementations and experimentations. This is widely addressed following low-cost and scalable methods such as analytical modeling and simulation. However, such methods are limited in capturing physical characteristics and network conditions in a realistic manner. Therefore, this paper presents an innovative IoT testbed system which facilitates practical experimentation of different IoT solutions in an effective environment. The testbed design was developed towards a general-purpose multidimensional support of different IoT properties including sensing, communication, gateway, energy management, data processing, and security. The implementation of the testbed was realized based on integrating a set of robust hardware components and developing a number of software modules. To illustrate its effectiveness, the testbed was utilized to experiment with energy efficiency of selected IoT communication technologies. This resulted in lower energy consumption using the Bluetooth Low Energy (BLE) technology compared to the Zigbee and 6LoWPAN technologies. A further evaluation study of the system was carried out following the Technology Acceptance Model (TAM). As the study results indicated, the system provides a simple yet efficient platform for conducting practical IoT experiments. It also had positive impact on users’ behavior and attitude toward IoT experimentation.

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Realization and use of a digital portable Weather Station - An integrated example of technological applications of low cost and high quality professional hardware platforms for innovative laboratory teaching in the classroom

10.5194/egusphere-egu2020-6070 ◽

2020 ◽

Author(s):

Pietro Crimi

Keyword(s):

Communication Networks ◽

Meteorological Data ◽

Low Cost ◽

Online Communication ◽

Lower Troposphere ◽

Mobile Systems ◽

Advanced Technology ◽

Weather Data ◽

Weather Station ◽

Laboratory Teaching

<p>As part of the innovation in the laboratory teaching of Natural Sciences, an experimental path of learning of Atmospheric Sciences and Microclimates is proposed in continuation and evolution, which was presented with a poster at the GIFT workshop 2017, an experience of project, construction and use of a mobile and portable Weather Station with digital features.By identifying the main parameters that measure the physical characteristics of the lower troposphere and the corresponding sensors responsible for detecting instantaneous weather data, a project was developed for the construction of a mini weather station with an assembly system of modular electronic components in "open source" , such as those of the "Arduino" platform (series of electronic boards equipped with a microcontroller). In this way, a device for controlling the main weather parameters (temperature, atmospheric pressure, relative humidity, ...) in real time in any part of the territory was achieved relatively quickly and easily.&#160;The hardware platform in pre-assembled version, with specific microcontrollers and USB interface for connections to the most advanced computer devices, together with the sensors, which can be acquired through the online network, allow you to create a completely inexpensive but absolutely professional, effective and efficient weather mobile system as well as easily transportable in various external and internal environments.&#160;The subsequent data collection, through visualization with advanced technology display and fast and online communication networks, by means of applications for mobile systems (tablets and smartphones), integrated by field observations, define the instantaneous weather and to process meteorological data in statistical terms with simple operations and graphs.</p>

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Towards Efficient Data Collection in Space-Based Internet of Things

Sensors ◽

10.3390/s19245523 ◽

2019 ◽

Vol 19 (24) ◽

pp. 5523 ◽

Cited By ~ 1

Author(s):

Changjiang Fei ◽

Baokang Zhao ◽

Wanrong Yu ◽

Chunqing Wu

Keyword(s):

Data Collection ◽

Internet Of Things ◽

Weather Data ◽

Data Set ◽

Sensory Data ◽

Spatiotemporal Correlation ◽

Exact Data ◽

Efficient Data ◽

Global Coverage ◽

Efficient Data Collection

Due to the strong anti-destructive ability, global coverage, and independent infrastructure of the space-based Internet of Things (S-IoT), it is one of the most important ways to achieve a real interconnection of all things. In S-IoT, a single satellite can often achieve thousands of kilometers of coverage and needs to provide data transmission services for massive ground nodes. However, satellite bandwidth is usually low and the uplink and downlink bandwidth is extremely asymmetric. Therefore, exact data collection is not affordable for S-IoT. In this paper, an approximate data collection algorithm is proposed for S-IoT; that is, the sampling-reconstruction (SR) algorithm. Since the uplink bandwidth is very limited, the SR algorithm samples only the sensory data of some nodes and then reconstructs the unacquired data based on the spatiotemporal correlation between the sensory data. In order to obtain higher data collection precision under a certain data collection ratio, the SR algorithm optimizes the sampling node selection by leveraging the curvature characteristics of the sensory data in time and space dimensions. Moreover, the SR algorithm innovatively applies spatiotemporal compressive sensing (ST-CS) technology to accurately reconstruct unacquired sensory data by making full use of the spatiotemporal correlation between the sensory data. We used a real-weather data set to evaluate the performance of the SR algorithm and compared it with two existing representative approximate data collection algorithms. The experimental results show that the SR algorithm is well-suited for S-IoT and can achieve efficient data collection under the condition that the uplink bandwidth is extremely limited.

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Low-cost Wireless Personal Weather Station for Rural Farmers

Transactions on Networks and Communications ◽

10.14738/tnc.91.9647 ◽

2021 ◽

Vol 9 (1) ◽

pp. 01-10

Author(s):

André Rodrigue Tchamda ◽

Merlain Boris Djousse K. ◽

Anselme Maffo Koumetio ◽

Mathias Fru Fonteh ◽

François Becau Pelap ◽

...

Keyword(s):

Data Analysis ◽

Wind Speed ◽

Rural Areas ◽

Low Cost ◽

Data Extraction ◽

Weather Data ◽

Weather Station ◽

Rural Farmers ◽

Remote Server ◽

File Formats

This document presents the design of a prototype of a low-cost personal weather station suitable for farmers in rural areas who are or may not be engaged in rudimentary agriculture. This prototype measure several weather data: temperature, relative humidity, wind speed, wind direction, rainfall. For further data analysis, these are transmitted for recording to a remote server via wireless communication. The server offers data extraction possibilities in multiple file formats. A prototyping of the personal weather station is designed and commissioned. An extract of the results over two days is presented in the results section of this document

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Low-Cost Automatic Weather Stations in the Internet of Things

Information ◽

10.3390/info12040146 ◽

2021 ◽

Vol 12 (4) ◽

pp. 146

Author(s):

Konstantinos Ioannou ◽

Dimitris Karampatzakis ◽

Petros Amanatidis ◽

Vasileios Aggelopoulos ◽

Ilias Karmiris

Keyword(s):

Deep Learning ◽

Internet Of Things ◽

Low Cost ◽

The Internet ◽

Climatic Data ◽

Time Data ◽

New Era ◽

Observation Systems ◽

Weather Stations ◽

The Internet Of Things

Automatic Weather Stations (AWS) are extensively used for gathering meteorological and climatic data. The World Meteorological Organization (WMO) provides publications with guidelines for the implementation, installation, and usages of these stations. Nowadays, in the new era of the Internet of Things, there is an ever-increasing necessity for the implementation of automatic observing systems that will provide scientists with the real-time data needed to design and apply proper environmental policy. In this paper, an extended review is performed regarding the technologies currently used for the implementation of Automatic Weather Stations. Furthermore, we also present the usage of new emerging technologies such as the Internet of Things, Edge Computing, Deep Learning, LPWAN, etc. in the implementation of future AWS-based observation systems. Finally, we present a case study and results from a testbed AWS (project AgroComp) developed by our research team. The results include test measurements from low-cost sensors installed on the unit and predictions provided by Deep Learning algorithms running locally.

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Naturally triggered persistent deep slab avalanches in western Canada Part II: weather trends from model forecasts

Journal of Glaciology ◽

10.1017/jog.2016.2 ◽

2016 ◽

Vol 62 (232) ◽

pp. 256-269 ◽

Cited By ~ 1

Author(s):

MICHAEL CONLAN ◽

BRUCE JAMIESON

Keyword(s):

Classification Tree ◽

Surface Wind ◽

Critical Parameters ◽

Wind Loading ◽

Weather Data ◽

Limited Area ◽

Weather Station ◽

Station Data ◽

Weather Station Data ◽

Weather Stations

ABSTRACTFor 175 difficult-to-forecast persistent deep slab avalanches, weather data were obtained from Global Environmental Multiscale (GEM) models produced by Environment Canada. The focus was to determine critical parameters and thresholds for avalanche forecasting from GEM and compare them with weather station data analyzed in Part I (Conlan and Jamieson, this issue). The high-resolution GEM-limited-area model (2.5 km resolution) forecasted higher median precipitation amounts than both the lower-resolution GEM15 (15 km resolution) and weather stations within a small dataset. Air temperatures were lower for both weather models compared with the weather station data, likely because of elevation differences. A multivariate classification tree created with GEM15 data correctly classified 29 of 36 avalanches by their primary cause-of-release, using a primary split of modelled solar warming of 5.9°C, 10 cm into the snowpack. For all 175 avalanches, GEM15 forecasted significantly less precipitation than observed at the weather stations, particularly with multi-day cumulative amounts. The majority of GEM15 surface wind speeds were between 0 and 10 km h−1, producing negligible wind loading amounts. The parameter values may be helpful for predicting future persistent deep slab avalanches. However, GEM output is not always representative of field conditions and should be used in conjunction with other sources.

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Consumer Grade Weather Stations for Wooden Structure Fire Risk Assessment

Sensors ◽

10.3390/s18103244 ◽

2018 ◽

Vol 18 (10) ◽

pp. 3244 ◽

Cited By ~ 2

Author(s):

Torgrim Log

Keyword(s):

Risk Assessment ◽

Relative Humidity ◽

Low Cost ◽

Fire Risk ◽

Weather Conditions ◽

Living Room ◽

Weather Station ◽

Fire Risk Assessment ◽

Weather Stations ◽

Dry Wood

During January 2014, Norway experienced unusually cold and dry weather conditions leading to very low indoor relative humidity (RH) in inhabited (heated) wooden homes. The resulting dry wood played an important role in the two most severe accidental fires in Norway recorded since 1923. The present work describes testing of low cost consumer grade weather stations for recording temperature and relative humidity as a proxy for dry wood structural fire risk assessment. Calibration of the weather stations relative humidity (RH) sensors was done in an atmosphere stabilized by water saturated LiCl, MgCl2 and NaCl solutions, i.e., in the range 11% RH to 75% RH. When calibrated, the weather station results were well within ±3% RH. During the winter 2015/2016 weather stations were placed in the living room in eight wooden buildings. A period of significantly increased fire risk was identified in January 2016. The results from the outdoor sensors compared favorably with the readings from a local meteorological station, and showed some interesting details, such as higher ambient relative humidity for a home close to a large and comparably warmer sea surface. It was also revealed that a forecast predicting low humidity content gave results close to the observed outdoor weather station data, at least for the first 48 h forecast.

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A Method Comparison Study between Open Source and Industrial Weather Stations

Engineering Proceedings ◽

10.3390/engproc2021009008 ◽

2021 ◽

Vol 9 (1) ◽

pp. 8

Author(s):

Evmorfia P. Bataka ◽

Georgios Miliokas ◽

Nikolaos Katsoulas ◽

Christos T. Nakas

Keyword(s):

Open Source ◽

Low Cost ◽

Method Comparison ◽

Measurement Range ◽

Weather Station ◽

Behavior Monitoring ◽

Smart Farming ◽

Weather Stations ◽

Method Comparison Study ◽

The University

Open-source devices are widespread and have been available to everyone over the past decade. The low cost of such devices boosts the creation of instruments for various applications such as smart farming, environmental monitoring, animal behavior monitoring, human health monitoring, etc. This research aims to use statistical methods to assess agreement and similarity in order to compare an open-source weather station that was constructed and programmed from scratch with an industrial weather station. The experiment took place in the experimental Greenhouses of the University of Thessaly, Velestino, Greece, for 7 consecutive days. The topology of the experiment consisted of 30 open-source weather stations and three industrials, creating three clusters with a ratio of 10 open-source to 1 industrial. The results revealed low to high agreement across the measurement range, with high variability, possibly due to factors that were not considered in the statistical model.

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