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"Untuk meningkatkan kualitas dan kuantitas data meteorologi di Indonesia, Badan Meteorologi Klimatologi Dan Geofisika (BMKG) terus mengembangkan Observasi cuaca otomatis. Saat ini BMKG memiliki beberapa alat otomatis, diantaranya: automatic weather station (AWS) sebanyak 63 unit serta automatic weather observation System (AWOS) sebanyak 165 unit, yang terdapat didalam ataupun diuar lingkungan Stasiun BMKG. Untuk mempermudah dalam pemantauan kondisi AWS, khususnya pada sistem sensor temperatur, tekanan, kelembaban dan curah hujan, diperlukan perangkat tambahan. Tambahan perangkat digunakan untuk memonitor dan memberi peringatan secara dini jika terjadi masalah dengan keempat sistem sensor tersebut. Hubungan secara fisis tiap unsur cuaca menjadi kunci untuk mendeteksi kondisi sistem sensor AWS yang akan dilatih dan diuji dengan menggunakan metode Artificial Neural Network (ANN). Berdasarkan pelatihan dan pengujian model Didapatkan 4 model ANN dengan akurasi baik hingga sangat baik yang dapat digunakan untuk mendeteksi kondisi AWS dalam sebuah klasifikasi (sistem sensor normal atau indikasi bermasalah) dengan menggunakan data realtime AWS.

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To improve the quality and quantity of meteorological data in Indonesia, Meteorology Climatology and Geophysics Agency of Indonesia (BMKG) is continuously developing automatic weather observations. Currently BMKG has 63 units Automatic Weather Station (AWS) and 165 units Automatic Weather Observation System (AWOS) both inside or outside of the BMKG Station environment.

To make the monitoring of AWS conditions easier, especially for temperature, pressure, relative humidity, and rainfall sensor systems, an additional system are needed. Additional system are used to monitor and provide early warning if there is a problem with the four sensor systems. The physical relationship of each weather element is the key to detecting the condition of the AWS sensor system which will be trained and tested using the Artificial Neural Network (ANN) method. Based on model training and testing, 4 ANN models with good to very good accuracy were obtained which can be used to detect AWS conditions in a classification (normal sensor system or error indication) using AWS realtime data."

"The Handbook of Advanced Lighting Technology is a major reference work on the subject of light source science and technology, with particular focus on solid-state light sources – LEDs and OLEDs – and the development of 'smart' or 'intelligent' lighting systems; and the integration of advanced light sources, sensors, and adaptive control architectures to provide tailored illumination which is 'fit to purpose.' The concept of smart lighting goes hand-in-hand with the development of solid-state light sources, which offer levels of control not previously available with conventional lighting systems. This has impact not only at the scale of the individual user, but also at an environmental and wider economic level. These advances have enabled and motivated significant research activity on the human factors of lighting, particularly related to the impact of lighting on healthcare and education, and the Handbook provides detailed reviews of work in these areas. The potential applications for smart lighting span the entire spectrum of technology, from domestic and commercial lighting, to breakthroughs in biotechnology, transportation, and light-based wireless communication. Whilst most current research globally is in the field of solid-state lighting, there is renewed interest in the development of conventional and non-conventional light sources for specific applications. This Handbook comprehensively reviews the basic physical principles and device technologies behind all light source types and includes discussion of the state-of-the-art. The book essentially breaks down into five major sections: Section 1: The physics, materials, and device technology of established, conventional, and emerging light sources, Section 2: The science and technology of solid-state (LED and OLED) light sources, Section 3: Driving, sensing and control, and the integration of these different technologies under the concept of smart lighting, Section 4: Human factors and applications, Section 5: Environmental and economic factors and implications"