Spraying disinfectants as a preventive measure to prevent the transmission of COVID-19 is still being carried out by officers manually by surrounding all parts of the building. Technological developments in the modern era can help and simplify this job by using drones or Unmanned Aerial Vehicle (UAV) to spray disinfectants indoors. With the use of UAVs, officers can spray remotely to reduce the number of officers and avoid transmission. In this paper, the researchers designed a UAV quadcopter using a 2200 KV BLDC motor controlled by the SP Racing F3 flight controller. This design has been able to be flown by carrying 200 ml of disinfectant which is ready to be sprayed. However, for a quadcopter to be able to lift loads that are greater than the BLDC motor specifications, the battery capacity and motor specifications need to be increased.

Permintaan beban yang bervariatif pada pendistribusian material melalui belt conveyor mengakibatkan kecepatan motor induksi berubah. Perubahan terjadi karena perbedaan torsi akibat perubahan beban. Hal tersebut mengakibatkan waktu pendistribusian material setiap perubahan beban akan berbeda. Untuk menghindari hal tersebut diperlukan sistem kontrol kecepatan yang mampu mempertahankan nilai setpoint antara belt conveyor bermuatan maksimum ataupun minimun. Sistem kontrol yang digunakan pada tulisan ini adalah sistem vektor kontrol dengan Variable Frequency Drive (VFD). Pada sistem ini kordinat-abc pada motor induksi tiga fasa diproyeksikan pada koordinat-dq yang diibaratkan berputar bersama dengan rotor. Dengan metode ini kecepatan lebih mudah dikendalikan dengan memanfaatkan Field Oriented Control (FOC). Untuk mengetahui pengaruh ini terhadap kecepatan motor induksi dilakukan simulasi dengan MATLAB/Simulink. Berdasarkan simulasi ini motor yang telah diberikan sistem kontrol mampu mempertahan kecepatannya pada nilai setpoint meskipun beban berubah secara drastis. Hal ini menunjukan bahwa sistem mampu mengatasi perubahan kecepatan pada belt conveyor akibat adanya perubahan beban.

Pandemi COVID-19 menyebabkan banyaknya masyarakat yang terdampak secara ekonomi akibat pembatasan kegiatan. Bantuan sosial dengan berbagai skema diberikan untuk menekan dampak yang dialami masyarakat, salah satu bantuan tersebut berupa Bantuan Sosial Beras (BSB). Mekanisme penyaluran bantuan dilakukan dari Bulog langsung kepada titik yang disepakati. Namun dalam kegiatannya proses pembagian seringkali memicu kerumunan bahkan tak jarang muncul korban akibat saling dorong hingga memicu meningkatnya kasus penularan COVID-19. Pencegahahan kerumunan dapat dilakukan dengan pembagian secara door to door. Namun dengan cara ini dibutuhkan petugas untuk mendatangi setiap rumah dan ketika penerima manfaat tidak di rumah, pengurusan untuk mendapatkan beras akan menjadi rumit. Pada kegiatan pengabdian kepada masyarakat Fakultas Teknik Universitas Andalas, diperkenalkan Anjungan Terima Mandiri Beras (ATM – B) berbasis RFID. Melalui Alat ini masyarakat yang terdaftar akan diberikan kartu RFID, masyarakat dapat mendekatkan kartu ke perangkat RFID yang terdapat pada ATM – B dan beras akan otomatis dikeluarkan sesuai takaran. Alat ini diharapkan mampu membantu melakukan pendistribusian beras kepada masyarakat, sehingga proses pendistribusian dapat dilakukan mandiri dengan mendatangi ATM – B yang terdekat pada waktu yang telah ditentukan. Dengan dirancangnya alat ini diharapkan mampu mengurangi jumlah petugas dalam menyalurkan beras, mengatasi kerumunan ditengah masyarakat dan menekan angka penularan COVID-19 saat bantuan sosial dibagikan

Measurement of electric charge on the battery in real-time cannot be separated from external noise and disturbances such as temperature and interference. An optimal State of Charge (SoC) estimator model is needed to make the estimation more accurate. To obtain the model, the battery was tested under room temperature conditions and at a temperature of 40oC to obtain a second-order RC model for the Li-Ion battery used. Based on the test data obtained, the data will be tested first using the Kalman Filter method to get an estimate of the State of Charge (SoC). Tests were carried out using MATLAB software. After the method was tested, the online SoC Estimator design began using the Raspberry Pi Single Board Computer (SBC). After that, the estimator will be tested first using data from offline measurements and then used in real-time (online) SoC estimation measurements. The Voc before the battery discharge test was 13.16 V and after the test, the measured Voc was 11.58 V. During the discharge the Voc was reduced by 1.58 V. While the discharge data from the battery manufacturer showed the reduced Voc during the discharge was 1.2V.

Measurement of electric charge on the battery in real-time cannot be separated from external noise and disturbances such as temperature and interference. An optimal State of Charge (SoC) estimator model is needed to make the estimation more accurate. To obtain the model, the battery was tested under room temperature conditions and at a temperature of 40oC to obtain a second-order RC model for the Li-Ion battery used. Based on the test data obtained, the data will be tested first using the Kalman Filter method to get an estimate of the State of Charge (SoC). Tests were carried out using MATLAB software. After the method was tested, the online SoC Estimator design began using the Raspberry Pi Single Board Computer (SBC). After that, the estimator will be tested first using data from offline measurements and then used in real-time (online) SoC estimation measurements. The Voc before the battery discharge test was 13.16 V and after the test, the measured Voc was 11.58 V. During the discharge the Voc was reduced by 1.58 V. While the discharge data from the battery manufacturer showed the reduced Voc during the discharge was 1.2V.