Package Reception Security System Using Face Recognition and Comparison Algorithms Method with Rasberry Pi Based on Internet of Things
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Abstract
In this research will use a Raspberry Pi for face processing. Raspberry Pi was chosen because the facial recognition process requires larger CPU processing. Then for input, use a webcam. Then it will be processed by the Raspberry Pi which will then open the door lock and the package can be taken by the buyer. Research Objective "a package receiving sistem using face recognition and comparison algorithms with a Raspberry Pi based on the internet of things" can make it easier for recipients to receive packages safely when the package recipient is not at home. As a result of this research, the author completed several things that became reference points to get maximum results with the most efficient model design possible. This sistem uses a webcam as input which is then processed using a comparison algorithm to compare the registered photos with the frames obtained from the webcam. Then the results will be sent to the website for anyone who tries to open the goods receipt safe to see.
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Aisah Putri, R., Kholis, N., & Baskoro, F. (2021). Automatic Packaging Conveyor Tracking System Based On Arduino Uno Using Photodiodes and SRF04 Ultrasonic Sensors. In Indonesian Journal of Electronics Engineering (Vol. 04). Retrieved from https://widuri.raharja.info/index.php?title=SI12
Ayu Nur Hidayati Putri, S., Brillian Kharisma, O., & Simaremare, H. (2023). Smart Packgaes Box Berbasis Internet Of Things Menggunakan Telegram Bot. JURNAL MEDIA INFORMATIKA BUDIDARMA, 8(2). doi: 10.30865/mib.v7i1.5517
Boyko, N., Basystiuk, O., & Shakhovska, N. (2018). Performance Evaluation and Comparison of Software for Face Recognition, Based on Dlib and Opencv Library. International Conference on Data Stream Mining & Processing.
Cahya Vikasari. (2018). Sistem Informasi Manajemen Pada Jasa Expedisi Pengiriman Barang Berbasis Web. JATISI, 4(2).
D.Srihari, B.Ravi Kumar, & K Yuvaraj. (2012). Development of Indian Coin based automatic shoe Polishing Machine using Raspberry pi with Open CV. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 1(3).
Farhan, M. (2022). Pembuatan Smart Box Penerima Paket Menggunakan Sensor HC-SR04 dan ESP32-CAM Berbasis IoT di Proactive Robotic.
Fitria, L., & Hermansyah, M. (2020). Implementasi Face Recognition pada Absensi Kehadiran Mahasiswa Menggunakan Metode Haar Cascade Classifier. InfoTekJar : Jurnal Nasional Informatika Dan Teknologi Jaringan, 4(2). doi: 10.30743/infotekjar.v4i2.2333
Ketut Arie Jaya, I Nyoman Putu Budiartha, & Ni Made Puspasutari Ujianti. (2020). Tanggungjawab Perusahaan Ekspedisi Terhadap Kerusakan Dan Kehilangan Barang Muatan Dalam Pengangkutan Darat. Jurnal Interpretasi Hukum, 1(1).
Monica, N., Sarkum, S., & Purnama, I. (2018). Aplikasi Data Mahasiswa Berbasis Android: Studi Pada Sekolah Tinggi Ilmu Ekonomi Labuhanbatu. IT JOURNAL RESEARCH AND DEVELOPMENT, 3(1), 43–53. doi: 10.25299/itjrd.2018.vol3(1).1849
Narang, N., & Bourlai, T. (2018). Deep Feature Learning for Classification When Using Single Sensor Multi-wavelength Based Facial Recognition Systems in SWIR Band. Springer.
Niswah, N., Suroso, S., & Soim, S. (2021). Rancang Bangun Sistem Peringatan Dini Bencana Hidrometeorologi Berbasis Internet of Thing (IoT) Di BMKG. Smatika Jurnal, 11(02), 153–159. doi: 10.32664/smatika.v11i02.593
Rakhmawati, N. A., Permana, A. E., Reyhan, A. M., & Rafli, H. (2021). Analisa Transaksi Belanja Online Pada Masa Pandemi COVID-19. Jurnal Teknoinfo, 15(1), 32. doi: 10.33365/jti.v15i1.868
Sanjaya, R. (2019). Sistem Keamanan Loker Menggubakan Biometrik Sidik Jari Bebasis Arduino. 1–84.
Ullo, S. L., & Sinha, G. R. (2020). Advances in smart environment monitoring systems using iot and sensors. In Sensors (Switzerland) (Vol. 20, Issue 11). MDPI AG. doi: 10.3390/s20113113