scholarly journals Low-Power Distributed Data Flow Anomaly-Monitoring Technology for Industrial Internet of Things

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2804 ◽  
Author(s):  
Han ◽  
Tian ◽  
Shi ◽  
Huang ◽  
Li
Keyword(s):  
Internet Of Things ◽  
Low Power ◽  
Monitoring System ◽  
Data Flow ◽  
Real Data ◽  
Communication Overhead ◽  
Distributed Data ◽  
Flow Monitoring ◽  
Industrial Use ◽  
The Relationship

. In recent years, the industrial use of the internet of things (IoT) has been constantly growing and is now widespread. Wireless sensor networks (WSNs) are a fundamental technology that has enabled such prevalent adoption of IoT in industry. WSNs can connect IoT sensors and monitor the working conditions of such sensors and of the overall environment, as well as detect unexpected system events in a timely and accurate manner. Monitoring large amounts of unstructured data generated by IoT devices and collected by the big-data analytics systems is a challenging task. Furthermore, detecting anomalies within the vast amount of data collected in real time by a centralized monitoring system is an even bigger challenge. In the context of the industrial use of the IoT, solutions for monitoring anomalies in distributed data flow need to be explored. In this paper, a low-power distributed data flow anomaly-monitoring model (LP-DDAM) is proposed to mitigate the communication overhead problem. As the data flow monitoring system is only interested in anomalies, which are rare, and the relationship among objects in terms of the size of their attribute values remains stable within any specific period of time, LP-DDAM integrates multiple objects as a complete set for processing, makes full use of the relationship among the objects, selects only one “representative” object for continuous monitoring, establishes certain constraints to ensure correctness, and reduces communication overheads by maintaining the overheads of constraints in exchange for a reduction in the number of monitored objects. Experiments on real data sets show that LP-DDAM can reduce communication overheads by approximately 70% when compared to an equivalent method that continuously monitors all objects under the same conditions.

scholarly journals Embedded Wireless Dissolved Oxygen Monitoring Based on Internet of Things Platform

2021 ◽  
pp. 363-368
Author(s):  
Wasana Boonsong ◽  
Keyword(s):  
Internet Of Things ◽  
Dissolved Oxygen ◽  
Water Temperature ◽  
Monitoring System ◽  
Pearson Correlation ◽  
The Social ◽  
Iot Platforms ◽  
Oxygen Monitoring ◽  
Dissolved Oxygen Monitoring ◽  
The Relationship

Recently, Internet of Things (IoT) applications are distributing into many areas, such as industry and agriculture. This article presents the embedded wireless Dissolved Oxygen (DO) monitoring system based on IoT platforms. The module contains two types of data sensing, which are water temperature and DO sensors. Both devices are embedded with a wireless IoT module using NodeMCU-ESP8266, an integration WiFi-Microcontroller on a single board. The proposed IoT-DO monitoring system detects information data from the aquaculture pond environment. Namely, the parameters studied are water temperature and DO values. The cloud internet network collects and stores the experimental data and link to the users. The relationship between both parameters is analyzed using Statistical Package for the Social Sciences based Pearson correlation coefficient theory. The findings found that the water temperature and DO values are negatively related, with a statistically significant .05. Water temperature is the principal affection to other parameters of water. In this work, the DO value is studied to relate the water temperature. It was found that when the water temperature increases, the DO decreases accordingly and vice versa.

Research and Design of Traffic Flow Monitoring System Based on Internet of Things

2013 ◽  
Vol 380-384 ◽  
pp. 786-789
Author(s):  
Jun Feng
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Traffic Flow ◽  
Monitoring System ◽  
Performance Monitoring ◽  
High Efficiency ◽  
Scheduling Algorithm ◽  
Flow Monitoring ◽  
Real Time Traffic ◽  
And Performance

The existing traffic flow monitoring system has some defects, including dispersed data collection, difficult to accurate and real-time monitor the vehicle motion process, low degree of all types of vehicle identification and limited monitoring performance. In order to solve all the problems above, this paper designs traffic flow monitoring system bases on Internet of Things. Using the core data collected by ZigBee wireless communication technique, the system adopts optimal scheduling algorithm to design the system. Simulation experiments are carried out on the basis of real-time collected by the system. The results show that the system achieves high efficiency and performance monitoring of the vehicle types, real-time classification, vehicle coordinate real-time positioning while operation, automatically receive real-time traffic data, and efficient scheduling.

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.

An Implementation On Smart Dustbin Monitoring System Using Internet of Things

2020 ◽  
Author(s):  
Afrin Khan ◽  
Aniket Nishad ◽  
Anuj Verma ◽  
Diwakar Mandal ◽  
Chandan Kumar Das ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Monitoring System
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