scholarly journals Voice Automation and Security Using Raspberry Pi 3

2021 ◽  
pp. 453-457
Author(s):  
Anjali Dalvi ◽  
Mohd. Ali Ansari ◽  
Anjali Tiwari ◽  
Rutuja Sonavane ◽  
Arti Bakshi
Keyword(s):  
Internet Of Things ◽  
Speech Synthesis ◽  
Application Programming Interface ◽  
Emerging Technology ◽  
Raspberry Pi ◽  
Text Format ◽  
Application Programming ◽  
Voice Biometrics ◽  
The Voice ◽  
Programming Interface

Internet of Things (IoT) globally is an emerging technology enabling the exchange of knowledge and services. But over the years, security in IoT has become an issue. This paper shows a way of including security to daily-based applications by the use of voice biometrics. The voice of a user is stored and authenticated using an API (Application Programming Interface) called “VoiceIT”. This method involves the use of Python as the main coding language and uses many libraries such as the Google Speech library for speech synthesis that converts a speech to a text format. The processing of the code is done using Raspberry Pi 3. The implementation of this experiment proves useful for increased security in an advanced IoT system.

scholarly journals Sistem Pengukur Curah Hujan sebagai Deteksi Dini Kekeringan pada Pertanian Berbasis Internet of Things (IoT)

2020 ◽  
Vol 20 (02) ◽  
pp. 131-135
Author(s):  
Satrio Setyo Laksono ◽  
N Nurgiyatna
Keyword(s):  
Social Media ◽  
Internet Of Things ◽  
Application Programming Interface ◽  
Raspberry Pi ◽  
Application Programming ◽  
Programming Interface

Hujan merupakan faktor penting dalam segala aspek kehidupan, tidak tentunya kedatangan hujan saat ini sangat berpengaruh terhadap kegiatan industri, terutama pada sektor pertanian. Dalam industri pertanian tinggi rendahnya curah hujan sangat berpengaruh dalam pengelolaan sumber daya dan juga sangat menentukan hasil panen yang akan didapati. Sebagai contoh curah hujan yang terlalu tinggi dapat menyebabkan gagal panen dikarenakan resiko terjadinya banjir yang membuat tanaman padi mati, begitu pula curah hujan yang terlalu sedikit dapat pula menyebabkan gagal panen dikarenakan kurangnya sumber air. Dengan adanya Inernet of Things (IoT) dan Social Media diharapkan dapat membantu para petani dalam mengelola sumber air untuk lahan pertanian mereka. Penelitian ini menggunakan metode eskperimental dengan percobaan langsung terhadap hujan. Raspberry pi 3 digunakan sebagai controller, sensor magnetik diterapkan sebagai pengukur curah hujan yang dihubungkan memalui interface GPIO pada raspberry pi 3, dan diteruskan pada API (Application Programming Interface) Telegram berupa bot sebagai sebuah pesan. Tampilan pengontrol berupa sebuah layar chat yang terdapat pada telegram yang dapat digunakan untuk mengirim perintah yang sudah disediakan.

scholarly journals Sentiment Analysis on Overseas Tweets on the Impact of COVID-19 in Indonesia

2021 ◽  
Vol 5 (2) ◽  
pp. 304-313
Author(s):  
Tigor Nirman Simanjuntak ◽  
Setia Pramana
Keyword(s):  
Big Data ◽  
Application Programming Interface ◽  
Text Format ◽  
Python Programming Language ◽  
Application Programming ◽  
Python Programming ◽  
Negative Sentiment ◽  
Analytical Tools ◽  
The Impact ◽  
Programming Interface

This study aims to conduct analysis to determine the trend of sentiment on tweets about Covid-19 in Indonesia from the Twitter accounts overseas on big data perspective. The data was obtained from Twitter in the period of April 2020, with the word query "Indonesian Corona Virus" from foreign user accounts in English. The process of retrieving data comes from Twitter tweets by crawling the text using Twitter's API (Application Programming Interface) by employing Python programming language. Twitter was chosen because it is very fast and easy to spread through status updates from and among the user accounts. The number of tweets obtained was 8,740 in text format, with a total engagement of 217,316. The data was sorted from the tweets with the largest to smallest engagement, then cleaned from unnecessary fonts and symbols as well as typo words and abbreviations. The sentiment classification was carried out by analytical tools, extracting information with text mining, into positive, negative, and neutral polarity. To sharpen the analysis, the cleaned data was selected only with the largest engagement until those with 100 engagements; then was grouped into 30 sub-topics to be analyzed. The interesting facts are found that most tweets and sub-topics were dominated by the negative sentiment; and some unthinkable sub-topics were talked by many users.

scholarly journals Towards a general application programming interface (API) for injection molding machines

2020 ◽  
Vol 6 ◽  
pp. e302
Author(s):  
Olga Ogorodnyk ◽  
Mats Larsen ◽  
Ole Vidar Lyngstad ◽  
Kristian Martinsen
Keyword(s):  
Injection Molding ◽  
Process Parameters ◽  
Data Exchange ◽  
Application Programming Interface ◽  
Raspberry Pi ◽  
Injection Molding Process ◽  
Process Data ◽  
Molding Process ◽  
Application Programming ◽  
Programming Interface

Injection molding is a complicated process, and the final part quality depends on many machine and process parameters settings. To increase controllability of the injection molding process, acquisition of the process data is necessary. This paper describes the architecture and development of a prototype of an open application programming interface (API) for injection molding machines (IMMs), which has the potential to be used with different IMMs to log and set the necessary process parameter values. At the moment, the API includes an implementation of EMI data exchange protocol and can be used with ENGEL IMMs with CC300 and RC300 controllers. Data collection of up to 97 machine and process parameters (the number might vary depending on the type of machine at hand), obtained from sensors installed in the machine by the manufacturer is allowed. The API also includes a module for the acquisition of data from additional 3d party sensors. Industrial Raspberry Pi (RevPi) was used to perform analog-to-digital signal conversion and make sensors data accessible via the API prototype. The logging of parameters from the machine and from sensors is synchronized and the sampling frequency can be adjusted if necessary. The system can provide soft real-time communication.

Sistem Pengawasan Aktifitas Penggunaan Smartphone Android

2018 ◽  
Vol 9 (1) ◽  
pp. 24-31
Author(s):  
Rudianto Rudianto ◽  
Eko Budi Setiawan
Keyword(s):  
Application Programming Interface ◽  
Third Party ◽  
Image Content ◽  
Image File ◽  
Application Programming ◽  
Index Terms ◽  
Programming Interface

Availability the Application Programming Interface (API) for third-party applications on Android devices provides an opportunity to monitor Android devices with each other. This is used to create an application that can facilitate parents in child supervision through Android devices owned. In this study, some features added to the classification of image content on Android devices related to negative content. In this case, researchers using Clarifai API. The result of this research is to produce a system which has feature, give a report of image file contained in target smartphone and can do deletion on the image file, receive browser history report and can directly visit in the application, receive a report of child location and can be directly contacted via this application. This application works well on the Android Lollipop (API Level 22). Index Terms— Application Programming Interface(API), Monitoring, Negative Content, Children, Parent.

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