Sistem Pengaman Rumah dan Peringatan Dini Kebakaran Berbasis SMS dengan Menggunakan Raspberry Pi

Author(s):  
Haris Isyanto ◽  
Dwi Arsito
Keyword(s):  

Seiring bertambahnya jumlah penduduk di Jakarta dan berkembangnya zaman maka tingkat kejahatan berupa pencurian atau perampokan dengan disertai pembakaran banyak terjadi, berdasarkan data statistic kriminal tahun 2013-2014 pelaku kejahatan pada hak milik / barang masih didominasi jenis kejahatan pencurian bermotor sebanyak 42.508, pencurian hak milik / barang sebanyak 46.064 dan data statistik tentang kebakaran tahun 2015 pun mencapai 695 kejadian, baik berupa akibat konsleting listrik, pembakaran sampah, tabung gas meledak dan lain sebagainya. Dalam hal ini maka di rancang sistem pengaman rumah dan peringatan dini kebakaran berbasis SMS gateway dengan Raspberry Pi yang di kombinasikan dengan mikrokontroler Arduino Uno, sensor asap MQ-7, sensor PIR HC-SR501, Solenoid door Lock dan modem GSM E173 sebagai media untuk mengirimkan pesan ke pemilik. Dalam pengujian sistem ini di lakukan perbagian terlebih dahulu kemudian dilakukan penggabungan semua sistem agar terlihat berjalan sesuai dengan rancangan yang sudah dibuat. Dalam pungujian sensor PIR jarak ukur pendeteksi gerak sejauh 3m agar tidak semua orang yang jauh dari area 3m tidak terdeteksi melihat area pada umumnya rumah sederhana yang kecil. Adapun pengujian pada sensor asap dengan media pipa yang dilubangi per 10cm sehingga terlihat data yang di ambil oleh sensor tersebut berdasarkan PPM yang di baca.

Ergodesign ◽  
2020 ◽  
Vol 2020 (1) ◽  
pp. 19-24
Author(s):  
Igor Pestov ◽  
Polina Shinkareva ◽  
Sofia Kosheleva ◽  
Maxim Burmistrov

This article aims to develop a hardware-software system for access control and management based on the hardware platforms Arduino Uno and Raspberry Pi. The developed software and hardware system is designed to collect data and store them in the database. The presented complex can be carried and used anywhere, which explains its high mobility.


2018 ◽  
Vol 14 (1) ◽  
Author(s):  
L.F. Tipán ◽  
J.A. Rumipamba
Keyword(s):  

El objeto de este documento es presentar un medidor de energia electrica inteligente con raspberry Pi y Arduino UNO, para visualizar el consumo electrico aproximado de un hogar tipo en tiempo real, mediante una aplicación Android y servidor web en la raspberry utilizando hojas de calculo en linea de google, porque aproximado debido a que no se hace un muestreo de voltaje sino que en base a parametros definidos se emplean valores establecidos. En la presente investigacion se muestra la arquitectura base y la metodologia empleada demostrando que los datos obtenidos con este sistema propuesto es muy parecido en comparacion con un sistema que se encuentra disponible en el mercado, especialmente europeo y norteamericano como lo es el sistema AEOTEC que utiliza protocolos z wave.


2021 ◽  
pp. 1-11
Author(s):  
Suphawimon Phawinee ◽  
Jing-Fang Cai ◽  
Zhe-Yu Guo ◽  
Hao-Ze Zheng ◽  
Guan-Chen Chen

Internet of Things is considerably increasing the levels of convenience at homes. The smart door lock is an entry product for smart homes. This work used Raspberry Pi, because of its low cost, as the main control board to apply face recognition technology to a door lock. The installation of the control sensing module with the GPIO expansion function of Raspberry Pi also improved the antitheft mechanism of the door lock. For ease of use, a mobile application (hereafter, app) was developed for users to upload their face images for processing. The app sends the images to Firebase and then the program downloads the images and captures the face as a training set. The face detection system was designed on the basis of machine learning and equipped with a Haar built-in OpenCV graphics recognition program. The system used four training methods: convolutional neural network, VGG-16, VGG-19, and ResNet50. After the training process, the program could recognize the user’s face to open the door lock. A prototype was constructed that could control the door lock and the antitheft system and stream real-time images from the camera to the app.


Webology ◽  
2021 ◽  
Vol 18 (Special Issue 04) ◽  
pp. 733-751
Author(s):  
D.M. Sheeba

Internet of Things enables many industries to connect to end customers and provide seamless products and services delivery. Due to easy access to network, availability of devices, penetration of IoT services exponentially Growing. Meanwhile, Ensuring the Data Security and Integrity of devices connected to network is paramount. In this work, we bring the efficient way of implementing Secure Algorithm for low powered devices and enhancing the encryption and decryption process. In addition to the data security, to enhance node integrity with less power, Authenticator and intermediate network manager introduced which will acts as a firewall and manager of data flow. To demonstrate the approach, same is implemented using low cost Arduino Uno, Raspberry Pi boards. Arduino Uno used to demonstrate low powered encryption process using EDIA Algorithm and raspberry pi used as nodal manager to manage the integrity of nodes in a low-powered environment. Data Security and Integrity is ensured by the way of enhanced Algorithm and Integrity through BlockChain and results are provided and discussed. Finally result and future enhancement are explained.


2021 ◽  
Author(s):  
Xiaomin Zhang ◽  
Mingyu Song ◽  
Yaohui Xu ◽  
Zhengwu Dai ◽  
Weicong Zhang
Keyword(s):  

Author(s):  
Kholidiyah Masykuroh ◽  
Fikra Titan Syifa ◽  
Gatot Rizky Setiyanto ◽  
Afifah Dwi Ramadhani ◽  
Danny Kurnianto ◽  
...  

Author(s):  
K. V. Usha Ramani

One of the crucial difficulties we aim to find in computer vision is to recognize items automatically without human interaction in a picture. Face detection may be seen as an issue when the face of human beings is detected in a picture. The initial step towards many face-related technologies, including face recognition or verification, is generally facial detection. Face detection however may be quite beneficial. A biometric identification system besides fingerprint and iris would likely be the most effective use of face recognition. The door lock system in this project consists of Raspberry Pi, camera module, relay module, power input and output, connected to a solenoid lock. It employs the two different facial recognition algorithms to detect the faces and train the model for recognition purpose


Author(s):  
Meiyanto Eko Sulistyo ◽  
Stephanus Hanurjaya ◽  
Muhammad Danang Prastowo

In the printing industry process, monitoring is necessary for quality control of the product. The making of the tool on this project serves to monitor the output of the production machine. This monitoring is done by detecting the product output from the production machine using Sensor E18 D80NK. When the sensor detects the output, the sensor sends a signal to the Arduino UNO R3 which will calculate the amount of output from the product. Arduino will send information of the number of outputs via a USB connection to a central computer that is a Raspberry Pi 3 model B. The Python program on Raspberry Pi will read input from each Arduino address and display the data in realtime. At the same time, the data will be stored as a text file. This text file contains the number of product output and the time of the output. The prototype of this tool has been successfully created and there is still much development to do.


Author(s):  
Anggit Damaz Istoko ◽  
Aulia Faqih Rifa'i

At a recent time, a computer-based queue machine, which is using the computer as both a client and a server, is rated to be less practical and inefficient. In this case, the queue machine will need a number of the computer as many as the locket and the network configuration. Given these points, the aim of this research is to build a practice and applicable queue machine. In the development of this system, the writer adopted the prototyping method. Acquiring Arduino Uno to convert the analog signal become a digital which will be shown in the LED P10, utilizing NodeMCU ESP8266 as a WiFi module, and adapting Raspberry Pi 3 as a server, this queue system expected to solve the problem before. In addition, to build the web, this queue system is using javascript and node.js as the software. This research derives a practice, easy to use, and portable queue machine because it uses wifi for their connection.


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