jasasewa alat meteorologi/ klimatologi - portable marine automatic weather station (pmaws) Metadatastasiun BMKG di Kota Bandung. Terdiri dari stasiun Automatic Weather Station (AWS), pos hujan kerjasama dan UPT. Data and Resources. Tahun 2016 - Metadata Stasiun BMKG CSV. AWS(Automatic Weather Stations) merupakan suatu peralatan atau sistem terpadu yang di disain untuk pengumpulan data cuaca secara otomatis serta di proses agar pengamatan menjadi lebih mudah. AWS ini umumnya dilengkapi dengan sensor, RTU (Remote Terminal Unit), Komputer, unit LED Display dan bagian-bagian lainnya. AWS dipasang pada ketinggian 2 Pengertian. Automatic weather station adalah serangkaian sensor-sensor meteorologi yang disusun secara terpadu dan secara otomatis mencatat data-data meteorologi (suhu, tekanan, kelembaban, penyinaran matahari, curah hujan, angin) yang kemudian menghasilkan pulsa - pulsa elektrik yang akan ditampung dan diubah dalam data logger sehingga AUTOMATICWEATHER STATION (AWS) BERBASIS MIKROKONTROLER TESIS Diajukan sebagai salah satu syarat untuk memperoleh gelar Magister Sains KANTON LUMBAN TORUAN (BMKG) as an observer of the weather. Key words: Sensor, microcontroller, Automatic Weather Station, portable, data 1 Automatic weather, Kanton Lumban Toruan, FMIPA UI, 2009. wonosaringawikab.id-Rabu (16/12) Badan Meteorologi Klimatologi dan Geofisika (BMKG) memasang alat pengukur cuaca otomatis (Automatic Weather Station/AWS) di Desa Wonosari Kecamatan Sine Kabupaten Ngawi.Sebelum melakukan pemasangan Pegawai BMKG berkoordinasi dengan Kepala Desa Wonosari,Hartanto dan perwakilan dari Kecamatan Sine. Akhirnya diputuskan tempat yang tepat yaitu didepan Kantor Desa ditingkatkan Bagi BMKG, dengan hadirnya AWS produk lokal yang mempunyai spesifikasi yang sama dengan produk impor, ketergantungan pada produk impor akan berkurang. II. METODOLOGI A. Pengukuran Kecepatan dan Arah Angin untuk AWS Automatic Weather Station (AWS), seperti yang ditampilkan pada Gambar 1, merupakan suatu sistem terpadu Alatini akan mengukur langsung radiasi yang dihasilkan oleh sinar matahari tanpa terhalang awan. Automatic Solar Radiation Station (ASRS) Dalam atmosfer bumi terdapat bermacam-macam radiasi seperti : 1. Direct Solar Radiation (S) yaitu radiasi langsung dari matahari yang sampai ke permukaan bumi. 2. AutomaticWeather Station (AWS) merupakan stasiun cuaca otomatis yang di desain untuk mengukur dan mencatat parameter-parameter meteorologi secara otomatis. AWS terdiri dari beberapa komponen yaitu sensor, data logger, sistem komunikasi, sistem catu daya, display, dan peralatan pendukung lainnya. Sensor yang digunakan pada aws yaitu : Sistem BadanMeteorologi Klimatologi dan Geofisika (BMKG) sejak tahun 2004 telah memasang sistem AWS (Automatic Weather Stations) di wilayah Jabodetabek. Fungsi sistem ini untuk mendeteksi adanya cuaca 255y. Automatic Weather Stations in an Edged Internet of Things IoT system publicationAutomatic 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...Context 1... on the literature [31] and our perspective, an Edged IoT system architecture has three 3 main layers, as illustrated in Figure 2, which are as follows Connected End devices at the edge of a network with embedded processing power, primitive intelligence, network connectivity, and sensing capabilities. ...... The technological advancement in weather predictions has shown the need for accurate measurement of atmospheric parameters which is of utmost importance to meteorologists. Of recent, there is a need for observing atmospheric weather parameters that will make scientist have access to real-time data they need to forecast or predict atmospheric weather conditions [2]. The need for accurate meteorological forecasts is on the rise because some sectors are in need of accurate weather prediction like the agriculture sector, maritime sector, and aviation sector. ...An atmospheric data acquisition device is designed to ease and improve on the current method of acquiring Temperature, Pressure, and Relative Humidity measurement at different altitudes. The proposed work aims to solve the problem of inadequate atmospheric data by monitoring atmospheric weather conditions using sensors while the microcontroller processes the data collected and relays it to the user. This research was carried out at the University of Uyo, between September 2018 and January, 2023. Considering that weather forecasting is of the utmost importance in our current society, the system has been built using a BME280 module for the atmospheric parameters acquisition, an ESP8266 as the microcontroller for Data processing, and a wireless module for processing and transfer of the data from the BME module, a NEO6M GPS module for longitude and latitude, a Li-ion cell to power the components and a TP4056 circuit to recharge the Li-ion cell. A web application was incorporated to help the user interact and access the data to enable ease of understanding and real-time logging of the data collected. This work is targeted toward the weather forecasting sector, agricultural sector, and individuals which may wish to gather information about the atmosphere for knowledge consumption. The results show that this device has a good performance for capturing atmospheric parameters for real-time monitoring purposes.... The use of current technologies is also included. Finally, the study presents a case study developed in AWS AgroComp project and its results [9]. The work of Kulkarni et al. is about the nature of a weather display method using low-cost components that even any electronics enthusiast could design. ...Industrialization and rapid urbanization in almost every country adversely affect many of our environmental values, such as our core ecosystem, regional climate differences and global diversity. The difficulties we encounter as a result of the rapid change we experience cause us to encounter many problems in our daily lives. The background of these problems is rapid digitalization and the lack of sufficient infrastructure to process and analyze very large volumes of data. Inaccurate, incomplete or irrelevant data produced in the IoT detection layer causes weather forecast reports to drift away from the concepts of accuracy and reliability, and as a result, activities based on weather forecasting are disrupted. A sophisticated and difficult talent, weather forecasting needs the observation and processing of enormous volumes of data. In addition, rapid urbanization, abrupt climate changes and mass digitization make it more difficult for the forecasts to be accurate and reliable. Increasing data density and rapid urbanization and digitalization make it difficult for the forecasts to be accurate and reliable. This situation prevents people from taking precautions against bad weather conditions in cities and rural areas and turns into a vital problem. In this study, an intelligent anomaly detection approach is presented to minimize the weather forecasting problems that arise as a result of rapid urbanization and mass digitalization. The proposed solutions cover data processing at the edge of the IoT and include filtering out the missing, unnecessary or anomaly data that prevent the predictions from being more accurate and reliable from the data obtained through the sensors. Anomaly detection metrics of five different machine learning ML algorithms, including support vector classifier SVC, Adaboost, logistic regression LR, naive Bayes NB and random forest RF, were also compared in the study. These algorithms were used to create a data stream using the time, temperature, pressure, humidity and other sensor-generated information.... The results are then compared to land use data from the CORINE land cover inventory. The methodology provided promising results, which can be further improved by applying machine learning methods such as artificial neural networks, random forests and expert systems [12,18,19], and the results can be used for the application of forest policy as well as decision making [20][21][22][23][24]. ... Konstantinos IoannouThe detection of possible areas for the application of agroforestry is essential and involves the usage of various technics. The recognition of forest types using satellite or aerial imagery is the first step toward this goal. This is a tedious task involving the application of remote sensing techniques and a variety of computer software. The overall performance of this approach is very good and the resulting land use maps can be considered of high accuracy. However, there is also the need for performing high-speed characterization using techniques that can determine forest types automatically and produce quick and acceptable results without the need for specific software. This paper presents a comprehensive methodology that uses Normalized Difference Vegetation Index NDVI data derived from the Moderate Resolution Imaging Spectroradiometer instrument MODIS aboard the TERRA satellite. The software developed automatically downloads data using Google Earth Engine and processes them using Google Colab, which are both free-access platforms. The results from the analysis were exported to ArcGIS for evaluation and comparison against the CORINE land cover inventory using the latest update 2018.... The last prediction results are compared with other models and found that this gives little more accuracy than the others. In the paper [12], the Authors reviewed the technology used for the implementation of automated weather stations is being made. In addition, the Authors also introduced the advanced computing such as IoT, Edge Computing, In-Depth Learning, Low Power WAN LPWAN, etc. using upcoming AWS-based viewing systems. ...... For the measurements of ambient temperature and humidity, a DHT22 sensor AM2302 Waveshare, Waveshare Electronics, Shenzhen, China is used, which is interfaced with the Raspberry Pi. DHT22 is a commonly used sensor in the prototyping phase of IoT Internet of Things system developments [29], which is capable of performing periodic measurements every around two seconds, which is adequate for the task. ...The emerging use of low-temperature plasma in medicine, especially in wound treatment, calls for a better way of documenting the treatment parameters. This paper describes the development of a mobile sensory device referred to as MSD that can be used during the treatment to ease the documentation of important parameters in a streamlined process. These parameters include the patient’s general information, plasma source device used in the treatment, plasma treatment time, ambient humidity and temperature. MSD was developed as a standalone Raspberry Pi-based version and attachable module version for laptops and tablets. Both versions feature a user-friendly GUI, temperature–humidity sensor, microphone, treatment report generation and export. For the logging of plasma treatment time, a sound-based plasma detection system was developed, initially for three medically certified plasma source devices kINPen MED, plasma care, and PlasmaDerm Flex. Experimental validation of the developed detection system shows accurate and reliable detection is achievable at 5 cm measurement distance in quiet and noisy environments for all devices. All in all, the developed tool is a first step to a more automated, integrated, and streamlined approach of plasma treatment documentation that can help prevent user variability.... In the same way, in the article [11] the author comments that, in Greece, there is a growing need for automated observation systems that provide scientists with the realtime data necessary to design and implement environmental policies. Therefore, this article reviews the technologies most currently used to implement weather stations, where they use the Internet of Things, Edge Computing, Deep Learning, LPWAN and more. ...Jeffry Ricaldi Cerdan Laberiano Andrade ArenasCurrently, pollution and global warming is a very controversial problem, due to the various consequences and effects it generates on health and the environment. There are studies that highlight that the main pollutants are due to human action that generates the extermination of certain ecosystems, as well as the increase in various acute and chronic diseases. The ecosystems most neglected by the authorities and the citizens are the wetlands, which can be seen reflected in the wetlands of Ventanilla, whose surface has been reduced from 1,500 to hectares due to overpopulation and contamination by the citizens themselves in recent years. These accessions endanger the extermination of the habitat of 126 birds and 27 species of native plants that inhabit a certain place, which is of great concern because these ecosystems are rapidly degrading. That is why, in the face of this problem, the design of a weather station applying the internet of things is proposed, which aims to inform the caretakers of the current state of the wetlands through a web server, where it will serve to carry out preventive actions. regarding the care of a certain ecosystem that are essential for the stabilization of CO2 emissions. This system is made up of the ESP32 platform, which will activate the emergency lights and a siren when the DHT 22, BMP180, ML8511 and MQ135 sensors detect abnormal values in temperature, humidity, atmospheric pressure, altitude, UV radiation and toxic gases.... In some cases, the low sensor cost criterion is formulated implicitly, as a low-cost assumption of the entire system Madokoro et al. [7], Shahadat et al. [19], Singh et al. [21], or as a remark that the lower cost of weather sensors directly translates into a larger number of weather stations Adityawarman and Matondang [2]. In many cases, the application of the low-cost criterion can be expected, based on the types of sensors used Mestre et al. [25], Chiba et al. [10], Nomura et al. [11], Hill et al. [13], Almalki et al. [9], Kim et al. [26], Kuo et al. [27], and Ioannou et al. [28]. ...... Low-Cost Sensors [25] stationary high resolution, stability over different weather conditions [7] mobile analysis based on literature review [19] stationary not specified [2] stationary not specified [21] stationary analysis based on literature review [22] stationary low cost [8] mobile weight, size, range, resolution, cost [9] both 1 reliability in high temperatures, energy efficiency [23] stationary low cost [20] portable not specified [26] stationary analysis based on literature review [27] stationary analysis based on literature review [28] stationary analysis based on literature review [24] stationary low cost this paper both 1 response time of a sensor in the cyber-physical subsystem, two defined factors of information accuracy 1 mobile, stationary. ...... However, modern low-cost sensors, calibrated by the manufacturers, are believed to be able to ensure getting measured data at good or, at least, sufficient accuracy. This means that in current weather stations, low-cost sensors are willingly used [2,[7][8][9][18][19][20][21][22][23][24][25][26][27][28], and was the premise for formulating the two minor criteria of sensor selection. ...Agnieszka ChodorekRobert Ryszard Chodorek Paweł SitekSmart-city management systems use information about the environment, including the current values of weather factors. The specificity of the urban sites requires a high density of weather measurement points, which forces the use of low-cost sensors. A typical problem of devices using low-cost sensors is the lack of legalization of the sensors and the resulting inaccuracy and uncertainty of measurement, which one can attempt to solve by additional sensor calibration. In this paper, we propose a different approach to this problem, the two-stage selection of sensors, carried out on the basis of both the literature pre-selection and experiments actual selection. We formulated the criteria of the sensor selection for the needs of the sources of weather information the major one, which is the fast response time of a sensor in a cyber-physical subsystem and two minor ones, which are based on the intrinsic information quality dimensions related to measurement information. These criteria were tested by using a set of twelve weather sensors from different manufacturers. Results show that the two-stage sensor selection allows us to choose the least energy consuming due to the major criterion and the most accurate due to the minor criteria set of weather sensors, and is able to replace some methods of sensor selection reported in the literature. The proposed method is, however, more versatile and can be used to select any sensors with a response time comparable to electric ones, and for the application of low-cost sensors that are not related to weather stations.... Stasiun pengamatan cuaca berfungsi pemantauan dan pengamatan cuaca dan perubahan kejadian alam berdasarkan pembacaan sensor terhadap kondisi suhu, temperatur, udara dan kelembapan suatu daerah pada kurun waktu tertentu [7]. Badan Meteorologi Klimatologi dan Geofisika BMKG sebagai institusi yang melakukan tugas pemantauan cuaca telah memiliki jaringan pengamatan cuaca secara otomatis atau Automatic Weather Station AWS yang tersebar di seluruh wilayah Indonesia [8]. ...... Stasiun pengamatan cuaca otomatis lebih dikenal dengan istilah AWS demikian juga dengan istilah di dokumen Guide to Meteorological Instruments and Methods of Observation Nomor 8 dari World Meteorological Organisation WMO [7], [9], [10], namun untuk membedakan kategori stasiun pengamatan tersebut BMKG membagi 3 tiga tipe stasiun. Stasiun pengamatan cuaca terdiri dari Automatic Rain Gauge ARG, Agroclimat Automatic Weather Station AAWS dan Automatic Weather Station AWS, dimana ketiganya hanya dibedakan dalam parameter cuaca yang diamati dan jumlah sensor yang dipasang. ...Stasiun Pengamatan Cuaca pada Badan Meteorologi Klimatologi dan Geofisika BMKG telah merapatkan jaringan stasiun pengamatan cuaca guna menghasilkan akurasi data yang lebih baik. BMKG memiliki kurang lebih 1000 dan jumlah ini masih jauh dari ideal untuk kerapatan jaringan pengamatan cuaca se-Indonesia. Stasiun pengamatan cuaca yang terbagi dalam 3 tiga type yaitu Automatic Rain Gauge ARG, Automatic Weather Station AWS dan Agroclimate Automatic Weather Station AAWS. Pemuktahiran sistem pengiriman data dari stasiun pengamat cuaca terhadap protokol pengiriman File Transfer Protocol FTP melalui modem General Packet Radio Service GPRS setiap 10 menit, dengan upgrade teknologi Internet of Things IoT perlu peninjauan terhadap kinerja operasional sistem komunikasi data. Karakteristik data yang kecil sangat cocok pada teknologi Internet of Things dengan menggunakan protokol Message Queuing Telemetry Transport MQTT guna monitoring data-data cuaca secara real-time. Berdasarkan hasil kajian dan penelitian dengan pengujian yang dilakukan terhadap metode komunikasi protokol FTP dengan protokol IoT MQTT pada stasiun AWS menggunakan analisa dengan metode PIECES Performance, Information, Economic, Control, Efisiency dan Service menunjukkan protokol MQTT yang berbasis IoT sebagai konsep komunikasi data yang tepat dimasa depan mengantikan protokol FTP... Assim, tecnologias digitais são alternativas ou complementos para análises tradicionais. Em IoT e Deep Learning há monitoramento de condições climáticas em estações meteorológicas automáticas, em tempo real, de baixo custo, com avançada transmissão de dados [15]. Uso de IoT associada a redes neurais para analisar fatores e emissões de gases poluentes dióxido e monóxido de carbono e dióxido de enxofre, a fim de reduzir efeito estufa [16]. ...... This study uses MAE, RMSE, and RMSLE to compare the performance of different models. Most studies use the above three indicators a lot for data comparison [38][39][40]. They are widely used to objectively assess the accuracy of a regression equation by analyzing differences between observations and estimates. ...Kyung-Su ChuCheong-Hyeon OhJung-Ryel ChoiByung-Sik KimIn recent years, Korea has seen abnormal changes in precipitation and temperature driven by climate change. These changes highlight the increased risks of climate disasters and rainfall damage. Even with weather forecasts providing quantitative rainfall estimates, it is still difficult to estimate the damage caused by rainfall. Damaged by rainfalls differently for inch watershed, but there is a limit to the analysis coherent to the characteristic factors of the inch watershed. It is time-consuming to analyze rainfall and runoff using hydrological models every time it rains. Therefore, in fact, many analyses rely on simple rainfall data, and in coastal basins, hydrological analysis and physical model analysis are often difficult. To address the issue in this study, watershed characteristic factors such as drainage area A, mean drainage elevation H, mean drainage slope S, drainage density D, runoff curve number CN, watershed parameter Lp, and form factor Rs etc. and hydrologic factors were collected and calculated as independent variables, and the threshold rainfall calculated by the Ministry of Land, Infrastructure and Transport MOLIT was calculated as a dependent variable and used in the machine learning technique. As for machine learning techniques, this study uses the support vector machine method SVM, the random forest method, and eXtreme Gradient Boosting XGBoost. As a result, XGBoost showed good results in performance evaluation with RMSE 20, MAE 14, and RMSLE and the threshold rainfall of the ungauged watersheds was calculated using the XGBoost technique and verified through past rainfall events and damage cases. As a result of the verification, it was confirmed that there were cases of damage in the basin where the threshold rainfall was low. If the application results of this study are used, it is judged that it is possible to accurately predict flooding-induced rainfall by calculating the threshold rainfall in the ungauged watersheds where rainfall-outflow analysis is difficult, and through this result, it is possible to prepare for areas vulnerable to flooding. Agency for Meteorology, Climatology, and Geophysics of the Republic of Indonesia BMKG is an Indonesian government agency responsible for providing a comprehensive meteorological information service regarding weather forecast information, early warning of severe weather, aviation and maritime weather information, and climate monitoring as well. In order to achieve those goals, BMKG maintains a network of surface observing stations manual and automatic, radiosondes, wind profiler radars and weather radars installed across Indonesia. In terms of surface observation, BMKG currently operates 141 surface observing stations, with 59 stations are registered to the Regional Basic Synoptic Networks RBSN and 19 stations are registered to Regional Basic Climatological Network RBCN.The majority of the observation equipment used at those stations is still conventional-manual type, including mercury or chart-based instruments, which are difficult to be integrated automatically. This paper describes BMKG's efforts to modernize its observations equipment and to integrate its surface observing stations network as had been set out in the BMKG's roadmap of surface observation network automation 2015-2019. It is expected that BMKG able to support the WMO policy in eliminating the use of mercury-containing instruments gradually before 2020, and able to increase its ability in supporting the implementation of the WMO Integrated Global Observing System WIGOS objectives in the Regional Association RA V and other regional and international activities. To read the full-text of this research, you can request a copy directly from the authors.... In general, automatic and manual measurements of weather data generally have an abnormal distribution, but the homogeneity test generally shows that both are homogeneous [14,[19][20][21][22]. The value of the difference between these two measurements is visible when using the calculation of the root mean square error, and correlation [13,[23][24][25]. ...The shift from manual weather measurements to automation is almost inevitable. When switching to AWS Automatic Weather Station, WMO requires parallel data testing between automatic and manual measurements to be performed. The purpose of this paper is to conduct a parallel test of AWS data using a simple statistical test that has been applied to three main weather parameters, namely temperature, pressure, humidity, rainfall, and wind direction and speed. The months of January and June were used as samples to represent the character of the wet and dry seasons in the Makassar monsoon area. The results of the analysis show that during the rainy season, only pressure and temperature are identical and homogeneous. Meanwhile, in the dry season, apart from these two parameters, humidity and wind speed are also homogeneous and rainfall is a non-homogeneous parameter in January and June. Both AWS and manual observations show that the influence of land-sea winds in Makassar is very strong. Considering that there are inhomogeneous parameters, it is highly recommended to test for a longer time, taking into account the season, the influence of other global phenomena, the effect of missing data and incorrect data testing various methods of homogeneity and characteristics in each place and their effect on has not been able to resolve any references for this publication.