scholarly journals Digital brain: Model-based framework for dependable electroencephalogram sensing and actuation in internet of things system

Author(s):  
R. J. Kavitha ◽  
Saravanan K. K.

<p>Real-time brain internet of thing (IoT) frameworks are expensive. But, creating a cheaper framework has been quickened incredibly by the superior investigation that's being done on virtual brain. The passing of an imperative individual on a mystery mission is considered delicate data and must be taken care of with as much security as conceivable. By guaranteeing this discreteness, the time taken for the message of their passing to reach the pertinent specialist is expanded to up to a few days. The time taken to provide the message is as well. These days, the advancements in equipment expanding the capacities of the virtual brain and of the wearable brain IoT sensors have made the advancement of various unused program systems conceivable for engineers to make valuable applications that combine the human brain with IoT. Different tactile pathways are too empowered for communications of the human brain with bigger measured data. The fundamental point of this extend is to transfer secret records onto the clouds safely.</p>

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xiang Yu ◽  
Chun Shan ◽  
Jilong Bian ◽  
Xianfei Yang ◽  
Ying Chen ◽  
...  

With the rapid development of Internet of Things (IoT), massive sensor data are being generated by the sensors deployed everywhere at an unprecedented rate. As the number of Internet of Things devices is estimated to grow to 25 billion by 2021, when facing the explicit or implicit anomalies in the real-time sensor data collected from Internet of Things devices, it is necessary to develop an effective and efficient anomaly detection method for IoT devices. Recent advances in the edge computing have significant impacts on the solution of anomaly detection in IoT. In this study, an adaptive graph updating model is first presented, based on which a novel anomaly detection method for edge computing environment is then proposed. At the cloud center, the unknown patterns are classified by a deep leaning model, based on the classification results, the feature graphs are updated periodically, and the classification results are constantly transmitted to each edge node where a cache is employed to keep the newly emerging anomalies or normal patterns temporarily until the edge node receives a newly updated feature graph. Finally, a series of comparison experiments are conducted to demonstrate the effectiveness of the proposed anomaly detection method for edge computing. And the results show that the proposed method can detect the anomalies in the real-time sensor data efficiently and accurately. More than that, the proposed method performs well when there exist newly emerging patterns, no matter they are anomalous or normal.


Author(s):  
Andika Fajar Isnanto ◽  
Atikah Surriani ◽  
Sri Lestari ◽  
Unan Yusmaniar Oktiawati

Smart Home is one of the popular technological advances and developed by researchers or academics because of its high potential to be implemented in various fields. Smart Home is an Internet of Things based technology, which means that by connecting to the internet everyone can connect whenever and wherever they are. With the presence of smart home, it can simplify human problems and limitations. This paper describes the design and prototype of smart Home based on Internet of Things Applications on Android. There is an android application that functions to control and monitor the smart home. By using NodeMCU, is used as a line communication device between users and smartphones. The use of databases in Firebase makes the data on the smart home always real-time active because it is connected to Google servers. We also develop an android application; thus smart home can be controlled by its owner. Keywords: Smart Home, Internet of Thing, Android, Firebase.


2019 ◽  
Vol 6 (1) ◽  
pp. 39-51
Author(s):  
Endang Sri Rahayu ◽  
Nurul Amalia

Diabetes merupakan penyakit “silent killer” yang ditandai dengan peningkatan kadar glukosa darahdan kegagalan sekresi insulin. World Health Organization (WHO) pada tahun 2016 menyatakanbahwa diabetes menduduki urutan ke-6 sebagai penyakit mematikan di Indonesia. Sehingga upayapencegahan dan penanganan diabetes perlu mendapat perhatian yang serius. Internet of Things (IoT)dapat dijadikan sarana penunjang dalam penanganan penyakit diabetes. Inovasi ini memungkinkanperangkat perawatan kesehatan terhubung dengan jaringan internet, sehingga data pasien dapatdiperbaharui dan diakses secara real-time. Selain mempermudah akses, penggunaan IoT juga akanmemberikan nilai tambah pada efisiensi biaya pelayanan kesehatan. Penelitian ini bertujuan untukmerancang software sistem monitoring gula darah berbasis web yang terintegrasi dengan IoT,sehingga pasien dapat melakukan pemeriksaan, konsultasi dengan dokter dan melihat data rekammedis dari jarak jauh. Data hasil pemeriksaan akan disimpan didalam cloud dan ditampilkan secaraonline. Penelitian ini menggunakan Node MCU ESP8266 sebagai mikrokontroller yang telahdilengkapi dengan modul WiFi, Thingspeak sebagai cloud, aplikasi online dengan “Diamons” sebagaidashboard yang mampu menampilkan presentasi data grafis, dibangun dengan bahasa HypertextPreprocessor (PHP) sebagai bahasa pemogramannya. Penelitian ini akan melibatkan pihak medisdalam pengambilan keputusan. Umpan balik yang diberikan kepada pasien berupa anjuran sepertiresep obat, pola makan, dan kegiatan fisik yang harus dilakukan oleh pasien.


Sign in / Sign up

Export Citation Format

Share Document