Hybrid driver monitoring system based on Internet of Things and machine learning

2021 ◽  
Author(s):  
Lian Zhu ◽  
Yijing Xiao ◽  
Xiang Li
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Monitoring System ◽  
Driver Monitoring

scholarly journals Cry Recognition for Infant Incubator Monitoring System Based on Internet of Things using Machine Learning

2021 ◽  
Vol 14 (1) ◽  
pp. 444-452
Author(s):  
Erwin Sutanto ◽  
◽  
Fahmi Fahmi ◽  
Wervyan Shalannanda ◽  
Arga Aridarma ◽  
...  
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Monitoring System ◽  
Smart Device ◽  
The Real ◽  
Current Technology ◽  
2D Pattern ◽  
Infant Incubator ◽  
Technology Trend

With the current technology trend of IoT and Smart Device, there is a possibility for the improvement of our infant incubator in responding to the real baby’s condition. This work is trying to see that possibility. First is by analyzing of open baby voice database. From there, a procedure to find out baby cry classification will be explained. The approach was starting with an analysis of sound’s power from that WAV files before going further into the 2D pattern, which will have features for the machine learning. From this work, around 85% accuracy could be achieved. Then together with sensors, it would be useful for infant incubator’s innovation by utilizing this proposed configuration.

scholarly journals On-farm welfare monitoring system for goats based on Internet of Things and machine learning

2020 ◽  
Vol 16 (7) ◽  
pp. 155014772094403
Author(s):  
Yuan Rao ◽  
Min Jiang ◽  
Wen Wang ◽  
Wu Zhang ◽  
Ruchuan Wang
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Real Time ◽  
Monitoring System ◽  
Animal Husbandry ◽  
Environmental Data ◽  
Software Systems ◽  
Data Detection ◽  
Livestock Farming ◽  
On Farm

Intensive animal husbandry is becoming more and more popular with the adoption of modern livestock farming technologies. In such circumstances, it is required that the welfare of animals be continuously monitored in a real-time way. To this end, this study describes one on-farm welfare monitoring system for goats, with a combination of Internet of Things and machine learning. First, the system was designed for uninterruptedly monitoring goat growth in a multifaceted and multilevel manner, by means of collecting on-farm videos and representative environmental data. Second, the monitoring hardware and software systems were presented in detail, aiming at supporting remote operation and maintenance, and convenience for further development. Third, several key approaches were put forward, including goat behavior analysis, anomaly data detection, and processing based on machine learning. Through practical deployment in the real situation, it was demonstrated that the developed system performed well and had good potential for offering real-time monitoring service for goats’ welfare, with the help of accurate environmental data and analysis of goat behavior.

Design of industrial internet of things system based on machine learning and artificial intelligence technology

2020 ◽  
pp. 1-11
Author(s):  
Xu Kun ◽  
Zhiliang Wang ◽  
Ziang Zhou ◽  
Wang Qi
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Internet Of Things ◽  
Monitoring System ◽  
Remote Monitoring ◽  
Industrial Equipment ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Test Platform ◽  
Artificial Intelligence Technology

For industrial production, the traditional manual on-site monitoring method is far from meeting production needs, so it is imperative to establish a remote monitoring system for equipment. Based on machine learning algorithms, this paper combines artificial intelligence technology and Internet of Things technology to build an efficient, fast, and accurate industrial equipment monitoring system. Moreover, in view of the characteristics of the diverse types of equipment, scattered layout, and many parameters in the manufacturing equipment as well as the complexity of the high temperature, high pressure, and chemical environment in which the equipment is located, this study designs and implements a remote monitoring and data analysis system for industrial equipment based on the Internet of Things. In addition, based on the application scenarios of the actual aeronautical weather floating platform test platform, this study combines the platform prototype system to design and implement a set of strong real-time communication test platform based on the Windows operating system. The test results show that the industrial Internet of Things system based on machine learning and artificial intelligence technology constructed in this paper has certain practicality.

scholarly journals Smart Crop Monitor using Internet of Things, Cloud, Machine Learning and Android App

2020 ◽  
Vol 9 (3) ◽  
pp. 3213-3217
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Monitoring System ◽  
Environmental Conditions ◽  
Crop Management ◽  
Android Application ◽  
Crop Monitoring ◽  
Android App

This paper describes a Smart Crop Monitoring system implemented using Internet of Things (IoT) for sensing environmental conditions and forwarding the data, Machine Learning to generate decisions for crop management based on the data, Cloud for storage and an Android application interface for operation of the system.

scholarly journals Machine Learning-Based Stealing Attack of the Temperature Monitoring System for the Energy Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Qiong Li ◽  
Liqiang Zhang ◽  
Rui Zhou ◽  
Yaowen Xia ◽  
Wenfeng Gao ◽  
...  
Keyword(s):  
Machine Learning ◽  
Control System ◽  
Internet Of Things ◽  
Monitoring System ◽  
Temperature Monitoring ◽  
Dynamics Simulation ◽  
Energy Output ◽  
Gradient Boosting ◽  
Energy Internet ◽  
Extreme Gradient Boosting

With the development of the Energy Internet of Things (EIoT), it is of great practical significance to study the security strategy and intelligent control system for solar thermal utilization system to optimize the operation efficiency and carry out intelligent dynamic adjustment. For buildings integrated with solar water heating systems, computational fluid dynamics simulation was used in analyzing the process of solar energy output. A method based on machine learning is proposed to predict energy conversion. Besides, the simulation and analysis are carried out in combination with the possible safety problems such as the vibration of the control system. This paper proposed a novel platform of EIoT for machine learning-based cybersecurity study and implemented the platform for the temperature monitoring system. After the evaluation of the machine learning-based cybersecurity study, the EIoT system demonstrated a high performance with the Extreme Gradient Boosting (XGBoost) training algorithm.

Implementing Internet of Things in a Remote Patient Medical Monitoring System

2018 ◽  
Vol 6 (8) ◽  
pp. 159 ◽  
Author(s):  
Ifeoma V. Ngonadi
Keyword(s):  
Internet Of Things ◽  
Monitoring System ◽  
Medical Records ◽  
Research Work ◽  
Healthcare Delivery ◽  
Vital Signs ◽  
Personal Digital Assistant ◽  
Computer Applications ◽  
Medical Monitoring ◽  
Remote Patient

The Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. Remote patient monitoring enables the monitoring of patients’ vital signs outside the conventional clinical settings which may increase access to care and decrease healthcare delivery costs. This paper focuses on implementing internet of things in a remote patient medical monitoring system. This was achieved by writing two computer applications in java in which one simulates a mobile phone called the Intelligent Personal Digital Assistant (IPDA) which uses a data structure that includes age, smoking habits and alcohol intake to simulate readings for blood pressure, pulse rate and mean arterial pressure continuously every twenty five which it sends to the server. The second java application protects the patients’ medical records as they travel through the networks by employing a symmetric key encryption algorithm which encrypts the patients’ medical records as they are generated and can only be decrypted in the server only by authorized personnel. The result of this research work is the implementation of internet of things in a remote patient medical monitoring system where patients’ vital signs are generated and transferred to the server continuously without human intervention.

Perancangan Sistem Informasi “DIAMONS” (Diabetes Monitoring System) Berbasis Internet of Things (IoT)

2019 ◽  
Vol 6 (1) ◽  
pp. 39-51
Author(s):  
Endang Sri Rahayu ◽  
Nurul Amalia
Keyword(s):  
Internet Of Things ◽  
World Health Organization ◽  
Real Time ◽  
Monitoring System ◽  
World Health ◽  
Health Organization ◽  
Diabetes Monitoring

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.

Detecting Abnormal Behavior of an IoT Device in the Network Based on a Traffic Model

Telecom IT ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 50-55
Author(s):  
D. Saharov ◽  
D. Kozlov
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Mobile Networks ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Abnormal Behavior ◽  
Traffic Model ◽  
The Internet ◽  
Wide Spread ◽  
The Internet Of Things

The article deals with the СoAP Protocol that regulates the transmission and reception of information traf-fic by terminal devices in IoT networks. The article describes a model for detecting abnormal traffic in 5G/IoT networks using machine learning algorithms, as well as the main methods for solving this prob-lem. The relevance of the article is due to the wide spread of the Internet of things and the upcoming update of mobile networks to the 5g generation.

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