Perancangan Sistem Kehadiran Face Recognition Menggunakan Mikrokomputer Berbasis Internet of Things

2020 ◽  
Vol 5 (2 Februari) ◽  
pp. 155-166
Author(s):  
Ahmad Roihan ◽  
Nina Rahayu ◽  
Danang Saputro Aji
Keyword(s):  
Face Recognition ◽  
Internet Of Things ◽  
Real Time ◽  
Raspberry Pi

Semua perusahaan menginginkan sistem kehadiran yang lebih baik di mana dapat meningkatkan tingkat kedisiplinan pegawai dalam kehadiran. Dalam hal ini, menjadi masalah yang harus dicari solusinya dan membutuhkan fasilitas atau perancangan berupa sistem kehadiran yang dapat memudahkan dalam melakukan absensi kehadiran dan mengurangi akan terjadinya kesalahan dan kecurangan. Penelitian ini mengembangkan sistem sebagai pemecahan masalah pada sistem kehadiran yang telah ada saat ini dengan sistem kehadiran dengan pengenalan wajah. Raspberry Pi digunakan sebagai mikro komputer untuk melakukan proses pengolahan data untuk mengaktifkan webcam yang akan mendeteksi wajah ketika gerakan telah terdeteksi oleh PIR sensor sebagai input serta perancangan menggunakan bahasa pemrograman Python yang dijalankan pada platform sistem operasi Raspbian. Tujuan dari penelitian ini yaitu  mampu menerapkan sistem yang dapat melakukan pembacaan wajah pegawai untuk input kehadiran secara real time.   Kata Kunci: Kehadiran, Raspberry, Face Recognition, Webcam, Python

scholarly journals Sistem Anti Maling Untuk Rumah Tinggal Menggunakan IoT Bluemix

2018 ◽  
Vol 3 (1) ◽  
pp. 55
Author(s):  
Griffani Megiyanto Rahmatullah ◽  
Muhammad Ayat ◽  
Wirmanto Suteddy
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Raspberry Pi ◽  
Home Security ◽  
Object Storage ◽  
Processing And Storage ◽  
Security Surveillance ◽  
Cloud Applications ◽  
Application Access ◽  
And Storage

Sistem keamanan rumah merupakan implementasi yang harus dilakukan untuk meningkatkan keamanan dari kejadian yang tidak diinginkan. Beberapa implementasi hanya memberikan notifikasi sederhana berupa alarm dan tidak menjadi bukti yang kuat apabila terjadi pencurian. Salah satu solusi yang dilakukan adalah penempatan kamera untuk memantau keamanan rumah secara real time diintegrasikan dengan penyimpanan cloud. Bluemix merupakan salah satu provider untuk aplikasi cloud yang memiliki layanan pengolahan dan penyimpanan data, akses aplikasi mobile, pengawasan serta Internet of Things (IoT). Sistem yang diimplementasikan adalah integrasi Raspberry Pi dengan layanan Bluemix untuk melakukan pengawasan keamanan rumah dan memberikan notifikasi kepada pengguna. Sistem mendeteksi jarak menggunakan sensor HC-SR04 terhadap objek dan apabila jarak melewati acuan, hal tersebut adalah indikasi terjadinya pencurian. Berikutnya sistem akan menyalakan buzzer sebagai keluaran suara dan mengaktifkan kamera untuk mengambil gambar lalu diunggah ke object storage Bluemix. Langkah berikutnya yaitu layanan IBM push notification memberikan notifikasi ke perangkat Android pengguna. Pengujian dilakukan dengan menghalangi pembacaan sensor sehingga terjadi indikasi pencurian. Hasilnya adalah sistem berhasil menyalakan buzzer, mengambil gambar lalu diunggah ke Bluemix, dan notifikasi berhasil masuk pada Android. Notifikasi diterima oleh file browser pada perangkat Android dan dilakukan sinkronisasi dengan object storage untuk melakukan pengunduhan berkas gambar yang telah diunggah sebelumnya.Kata kunci: Bluemix, Raspberry Pi, object sorage, IBM push notification Home security system is an implementation that needs to be done to improve the security of unwanted events. Some implementations only provide a simple notification such as alarm and cannot become strong evidence in case of theft. One of the solutions is camera placement to monitor home security in real time integrated with cloud storage. Bluemix is a provider for cloud applications that have data processing and storage services, mobile application access, monitoring and Internet of Things (IoT). System implemented was integration of Raspberry Pi with Bluemix services to conduct home security surveillance and provide notification to user. System detected distance using HC-SR04 sensor to object and if distance passes the reference, it was an indication of theft. Next, system will turned on buzzer as a sound output and activating the camera to take picture and uploaded to Bluemix Object Storage. Next step was IBM push notification service giving notification to user's Android device. The testing was done by blocking the sensor readings so that there was an indication of theft. The result was system succeeded in turning on the buzzer, taking pictures, uploading pictures to Bluemix, and notification successfully logged on Android. Notifications are received by the file browser on Android device and synchronized with object storage to download image files that have been uploaded previously.Keywords: Bluemix, Raspberry Pi, object storage, IBM push notification 

scholarly journals Real-Time Internet Based Attendance Using Face Recognition System

2018 ◽  
Vol 7 (3.15) ◽  
pp. 174 ◽  
Author(s):  
Yuslinda Wati Mohamad Yusof ◽  
Muhammad Asyraf Mohd Nasir ◽  
Kama Azura Othman ◽  
Saiful Izwan Suliman ◽  
Shahrani Shahbudin ◽  
...  
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
Recognition System ◽  
Ease Of Use ◽  
Cloud Services ◽  
Raspberry Pi ◽  
Student Attendance ◽  
Online Student ◽  
Internet Server ◽  
Face Recognition System

This project focuses on face recognition implementation in creating fully automated attendance system with a cloud. Cloud services will provide a useful information regarding the attendance such as attendance summary performance and visualizing the data into graph and chart. In this study, we aim to create an online student attendance database, interfaced with a face recognition system based on raspberry pi 3 model B. A graphical user interface (GUI) will provide ease of use for data analysis on the attendance system. This work used open computer vision library and python for face recognition system combined with SFTP to establish connection to an internet server which runs on PHP and Node.js. The results showed that by interfacing a face recognition system with a server, a real-time attendance system can be built and be monitored remotely.  

scholarly journals INTERNET OF THINGS (IOT) BASED ADVANCED ONLINE EXAMINATION USING RASPBERRY PI

2020 ◽  
Vol 5 (5) ◽  
pp. 26-32
Author(s):  
Kunal Pawar ◽  
Pravin Latane
Keyword(s):  
Face Recognition ◽  
Internet Of Things ◽  
Raspberry Pi ◽  
Alarm System ◽  
Iot Applications ◽  
System A ◽  
Implementation Techniques ◽  
Online Examination ◽  
On Line ◽  
Exam System

In this research we have proposed IOT based advanced Online examination using Raspberry pi for Alarm system and border security. With the event of recent education, considering the defect of current online exam system, a replacement projection of online exam system primarily based on Raspberry pi IOT is projected, and also the key implementation techniques and ways also are represented. Internet of Things (IOT) has provided a promising chance to make powerful Examination systems and applications by leverage the growing omnipresence of wireless, RFID mobile and detector devices. a large vary of IOT applications are developed in recent years. In a shot to grasp the event of IOT in on-line examination, here we tend to propose this analysis of IOT, IOT key facultative technologies, major IOT applications in on-line examination and identifies analysis trends and challenges. Here we tend to introduce all the examiner details square measure holds on within the server. Then if somebody needs to starts on-line examination, 1st they ought to apply face recognition (in Open CV based) technique. as a result of it slow unwanted person conjointly enter to Wright the examination, thus this can be the simplest thanks to known any culprits square measure found or not. Then examination enter to Wright the exam, here conjointly I am apply some security. Currently a day’s already queries square measure hold on within the on-line or any paper written copy.

scholarly journals Implementation of IoT in Agriculture

2021 ◽  
Author(s):  
B. Mohamed Arafath Rajack ◽  
N. Subramanian ◽  
N. Arun Pragadesh ◽  
R. Suvanesh ◽  
S. Vignesh
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Mobile Application ◽  
Raspberry Pi ◽  
Modern World ◽  
The Real ◽  
Agriculture Sector ◽  
The World ◽  
Potential Pest ◽  
World Agriculture

In this modern world agriculture is one of the major booming sectors around the world. In India around 60 percent of GDP comes from agriculture sector alone. Also, around the world there are many technologies showing up in the field of agriculture. In this paper proposed a technology by means of which potential pest attack in the crops can be detected and the respective pesticide is also sprayed as well. Along with these there is a range of sensor employed in the field connected to the controller that will take the real time values from the field and can be displayed in the respective screen (monitor or mobile screen) by means of technology called IOT (Internet of Things). Raspberry-pi is used as the controller to perform IoT. system is linked with an application called “cain” Which allows us to display various values of sensors in the monitor or in mobile application.

scholarly journals Vision based Office Automation and Security System using Machine Learning and Internet of Things

2018 ◽  
Vol 7 (2.24) ◽  
pp. 42
Author(s):  
Amber Goel ◽  
Apaar Khurana ◽  
Pranav Sehgal ◽  
K Suganthi
Keyword(s):  
Machine Learning ◽  
Computer Vision ◽  
Face Recognition ◽  
Internet Of Things ◽  
Office Automation ◽  
Detection Algorithm ◽  
Machine Learning Algorithms ◽  
Human Detection ◽  
Raspberry Pi ◽  
Efficient Tool

The paper focuses on two areas, automation and security. Raspberry Pi is the heart of the project and it is fuelled by Machine Learning Algorithms using Open CV and Internet of Things. Face recognition uses Linear Binary Pattern and if an unknown person uses their workstation, a message will be sent to the respective person with the photo of the person who uses the workstation. Face recognition is also being used for uploading attendance and switching ON and OFF appliances automatically. During un-official hours, A Human Detection algorithm is being used to detect the human presence. If an unknown person enters the office, a photo of the person will be taken and sent to the authorities. This technology is a combination of Computer Vision, Machine learning and Internet of things, that serves to be an efficient tool for both automation and security.  

scholarly journals An internet of things (IoT)-based optimum tea fermentation detection model using convolutional neural networks (CNNs) and majority voting techniques

2021 ◽  
Vol 10 (2) ◽  
pp. 153-162
Author(s):  
Gibson Kimutai ◽  
Alexander Ngenzi ◽  
Said Rutabayiro Ngoga ◽  
Rose C. Ramkat ◽  
Anna Förster
Keyword(s):  
Neural Networks ◽  
Internet Of Things ◽  
Real Time ◽  
Convolutional Neural Networks ◽  
Colour Change ◽  
Black Tea ◽  
Majority Voting ◽  
Raspberry Pi ◽  
Deep Convolutional Neural Networks ◽  
Precision And Accuracy

Abstract. Tea (Camellia sinensis) is one of the most consumed drinks across the world. Based on processing techniques, there are more than 15 000 categories of tea, but the main categories include yellow tea, Oolong tea, Illex tea, black tea, matcha tea, green tea, and sencha tea, among others. Black tea is the most popular among the categories worldwide. During black tea processing, the following stages occur: plucking, withering, cutting, tearing, curling, fermentation, drying, and sorting. Although all these stages affect the quality of the processed tea, fermentation is the most vital as it directly defines the quality. Fermentation is a time-bound process, and its optimum is currently manually detected by tea tasters monitoring colour change, smelling the tea, and tasting the tea as fermentation progresses. This paper explores the use of the internet of things (IoT), deep convolutional neural networks, and image processing with majority voting techniques in detecting the optimum fermentation of black tea. The prototype was made up of Raspberry Pi 3 models with a Pi camera to take real-time images of tea as fermentation progresses. We deployed the prototype in the Sisibo Tea Factory for training, validation, and evaluation. When the deep learner was evaluated on offline images, it had a perfect precision and accuracy of 1.0 each. The deep learner recorded the highest precision and accuracy of 0.9589 and 0.8646, respectively, when evaluated on real-time images. Additionally, the deep learner recorded an average precision and accuracy of 0.9737 and 0.8953, respectively, when a majority voting technique was applied in decision-making. From the results, it is evident that the prototype can be used to monitor the fermentation of various categories of tea that undergo fermentation, including Oolong and black tea, among others. Additionally, the prototype can also be scaled up by retraining it for use in monitoring the fermentation of other crops, including coffee and cocoa.

scholarly journals Rancang Bangun Sistem Monitoring Dan Controlling Tambak Udang Windu Dengan Konsep Internet Of Things Menggunakan Protokol Message Queuing Telemetry Transport

2020 ◽  
Vol 5 (1) ◽  
pp. 137
Author(s):  
Dania Eridani ◽  
Eko Didik Widianto ◽  
Nur Kholid
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Raspberry Pi

Udang windu merupakan salah satu jenis udang asli dari Indonesia. Pembudidayaan udang windu sangat dipengaruhi oleh kualitas air pada tambak udang windu. Berdasarkan faktor tersebut, maka dibuatlah sistem yang mampu memantau dan mengontrol kualitas air pada tambak udang windu secara kontinyu dan real-time menggunakan konsep Internet of Things dengan protokol Message Queuing Telemetry Transport. Sistem yang dibangun terdiri dari 2 bagian, yang pertama adalah NodeMCU sebagai primary node yang terhubung dengan sensor (HC-SR04, SEN0161, dan DS18B20) untuk pemantauan kualitas air dan aktuator (motor DC sebagai kincir air). Bagian kedua adalah Raspberry Pi 3 Model B sebagai MQTT broker dan berfungsi untuk mengirimkan hasil pembacaan sensor menuju database. Hasil dari penelitian ini adalah sistem dapat memantau kualitas air dan juga melakukan kontrol terhadap kincir air melalui aplikasi berbasis website. Primary node juga bisa berkomunikasi dengan broker melalui protokol MQTT.

scholarly journals Real Time Face Recognition using Raspberry Pi

2020 ◽  
Vol 176 (33) ◽  
pp. 1-4
Author(s):  
Sanchit Dass ◽  
Mohammed Sadrulhuda ◽  
Navaz Pasha ◽  
Nishant Nayan ◽  
Jyothi S
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
Raspberry Pi
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