scholarly journals A Wireless Network for Collection and Synthesis of Mobile Mesoscale Weather Observations

2004 ◽  
Vol 21 (11) ◽  
pp. 1659-1670 ◽  
Author(s):  
Conrad L. Ziegler ◽  
Douglas Kennedy ◽  
Erik N. Rasmussen
Keyword(s):  
Real Time ◽  
Wireless Network ◽  
Field Experiments ◽  
The Internet ◽  
Field Observations ◽  
Time Data ◽  
Digital Network ◽  
Weather Observations ◽  
Instrumented Vehicles ◽  
Gathering Data

Abstract This paper reports the development of a wireless network of instrumented vehicles and aircraft for the real-time collection and synthesis of their mobile weather observations in mesoscale field experiments. The mobile digital network (MDN) utilizes 900-MHz radio frequency modem technology, enabling real-time data transmissions at up to 115 kbit s−1 across a domain of about 40 km on a side. The effective throughput of the network of multiple mobile units is about 40 kbit s−1 due to overhead from data quality checking and acknowledgment that data have been received. After gathering data from mobile observing platforms at a centrally located mobile command post, both image products and data are then uplinked via geostationary satellite at about 80 kbit s−1 and served to the Internet. The first application of the MDN was to mobile field observations obtained during the International H2O Project (IHOP).

Secure Real-time Data Access Using Two-Factor Authentication Scheme for the Internet of Drones

2021 ◽  
Author(s):  
Haqi Khalid ◽  
Shaiful Jahari Hashim ◽  
Sharifah Mumtazah Syed Ahamed ◽  
Fazirulhisyam Hashim ◽  
Muhammad Akmal Chaudhary
Keyword(s):  
Real Time ◽  
Data Access ◽  
Authentication Scheme ◽  
The Internet ◽  
Time Data ◽  
Real Time Data

scholarly journals A Real-Time Weed Mapping and Precision Herbicide Spraying System for Row Crops

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4245 ◽  
Author(s):  
Yanlei Xu ◽  
Zongmei Gao ◽  
Lav Khot ◽  
Xiaotian Meng ◽  
Qin Zhang
Keyword(s):  
Real Time ◽  
Field Experiments ◽  
Particle Swarm ◽  
Error Rates ◽  
Integrated System ◽  
Central Processor ◽  
Time Data ◽  
Weed Detection ◽  
Row Crops ◽  
Weed Mapping

This study developed and field tested an automated weed mapping and variable-rate herbicide spraying (VRHS) system for row crops. Weed detection was performed through a machine vision sub-system that used a custom threshold segmentation method, an improved particle swarm optimum (IPSO) algorithm, capable of segmenting the field images. The VRHS system also used a lateral histogram-based algorithm for fast extraction of weed maps. This was the basis for determining real-time herbicide application rates. The central processor of the VRHS system had high logic operation capacity, compared to the conventional controller-based systems. Custom developed monitoring system allowed real-time visualization of the spraying system functionalities. Integrated system performance was then evaluated through field experiments. The IPSO successfully segmented weeds within corn crop at seedling growth stage and reduced segmentation error rates to 0.1% from 7.1% of traditional particle swarm optimization algorithm. IPSO processing speed was 0.026 s/frame. The weed detection to chemical actuation response time of integrated system was 1.562 s. Overall, VRHS system met the real-time data processing and actuation requirements for its use in practical weed management applications.

scholarly journals Analisa Real-Time Data log honeypot menggunakan Algoritma K-Means pada serangan Distributed Denial of Service

Repositor ◽  
2020 ◽  
Vol 2 (5) ◽  
pp. 541
Author(s):  
Denni Septian Hermawan ◽  
Syaifuddin Syaifuddin ◽  
Diah Risqiwati
Keyword(s):  
Real Time ◽  
Data Storage ◽  
Denial Of Service ◽  
The Internet ◽  
Distributed Denial Of Service ◽  
Time Data ◽  
Local Networks ◽  
Real Time Data ◽  
Internet Networks ◽  
Data Log

AbstrakJaringan internet yang saat ini di gunakan untuk penyimpanan data atau halaman informasi pada website menjadi rentan terhadap serangan, untuk meninkatkan keamanan website dan jaringannya, di butuhkan honeypot yang mampu menangkap serangan yang di lakukan pada jaringan lokal dan internet. Untuk memudahkan administrator mengatasi serangan digunakanlah pengelompokan serangan dengan metode K-Means untuk mengambil ip penyerang. Pembagian kelompok pada titik cluster akan menghasilkan output ip penyerang.serangan di ambil sercara realtime dari log yang di miliki honeypot dengan memanfaatkan MHN.Abstract The number of internet networks used for data storage or information pages on the website is vulnerable to attacks, to secure the security of their websites and networks, requiring honeypots that are capable of capturing attacks on local networks and the internet. To make it easier for administrators to tackle attacks in the use of attacking groupings with the K-Means method to retrieve the attacker ip. Group divisions at the cluster point will generate the ip output of the attacker. The strike is taken as realtime from the logs that have honeypot by utilizing the MHN.

Testing MANET Protocol using Zigbee based Xbee Modules

2016 ◽  
Vol 3 (2) ◽  
pp. 441
Author(s):  
S. Sundar ◽  
Piyush Arora ◽  
Sarthak Agrawal ◽  
R. Kumar ◽  
Harish M. Kittur
Keyword(s):  
Wireless Sensor Network ◽  
Internet Of Things ◽  
Mobile Phone ◽  
Real Time ◽  
Sensor Network ◽  
Wireless Network ◽  
Wireless Sensor ◽  
The Internet ◽  
Popular Approach ◽  
The Internet Of Things

<p>In the last few years,there has been big interest in adhoc wireless network as they have tremendous military and commercial potential[1].Traditionally to test various parameters in the MANET , the most popular approach is to use mobile phone and Laptops and use the popular WIFI based protocol . But in the recent years there is a huge attraction towards the Internet Of things and specifically wireless sensor network. In this paper we are going to test the MANET protocol using zigbee based XBee modules specifally to determine the Range and Throughput of the Xbee netowork using XCTU Software . The sensor network will be deployed in the car parking application to see the parameters in the real time and dynamically see the sustainability of the network .The network is being designed keeping in mind that the nodes are mobile and at the same time the network does not require a standard infrastructure.</p>

Application of Real-Time Monitoring and Data Web Sharing to Landslides

2012 ◽  
Vol 166-169 ◽  
pp. 2787-2793
Author(s):  
Hong De Wang ◽  
Qi Lang Le ◽  
Xiu Yuan Yang ◽  
You Long Gao
Keyword(s):  
Communication Network ◽  
Real Time ◽  
Communication Technologies ◽  
The Internet ◽  
Massive Data ◽  
Real Time Monitoring ◽  
Time Data ◽  
Geologic Hazard ◽  
Data Elements ◽  
Central Station

Acquiring instant information and sharing massive data are indispensable elements in social informatization. Real-time monitoring is realized with the support of computer and communication technologies. The monitoring facilities which are controlled by communication network terminal computers would collect and transfer data according to established procedures or real-time instructions. That is, data could be acquired under all weather and no duty conditions. Then the acquired massive data could be widely shared by issuing on Internet Web. This whole procedure is called real-time monitoring. Demonstration station for real-time monitoring and prewarning is just used to issue monitoring instructions, collect and transfer real-time data through GPRS wireless network between local monitoring stations and central station on the basis of computer and modern communication technologies. So the monitoring data elements could be gathered on central station server computer through communication network, and then be Web published and shared through the connection of central station sever computer and the Internet. Thus, informatization for landslides monitoring could be realized, and information could be optimally utilized. The geologic hazard monitoring and prewarning demonstration station in Wushan County was a good example of real-time monitoring and data Web sharing for landslides, which has greatly improved the level of geologic hazard monitoring and prewarning in China.

IoT4Emergency

2021 ◽  
Vol 46 (1) ◽  
pp. 33-36
Author(s):  
Julie Dugdale ◽  
Mahyar T. Moghaddam ◽  
Henry Muccini
Keyword(s):  
Internet Of Things ◽  
Emergency Management ◽  
Real Time ◽  
International Workshop ◽  
The Internet ◽  
Time Data ◽  
Time Requirements ◽  
Safety Systems ◽  
Crises Management ◽  
The Internet Of Things

The increasing natural and man-induced disasters such as res, earthquakes, oods, hurricanes, overcrowding, or pandemic viruses endanger human lives. Hence, designing infrastructures to handle those possible crises has become an ever-increasing need. The Internet of Things (IoT) has changed our approach to safety systems by connecting sensors and providing real-time data to managers, rescuers, and endangered people. IoT systems can monitor and react to progressive disasters, people's movements and their behavioral patterns. The community faces challenges in using IoT for crises management: i) how to take advantage of technological advancements and deal with IoT resources installation issues? ii) what environmental contexts should be considered while designing IoT-based emergency handling systems? iii) how should system design comply with various levels of real-time requirements? This paper reports on the results of the First International Workshop on Internet of Things for Emergency Management (IoT4Emergency 2020), which speci cally focuses on challenges and envisioned solutions in using smart connected systems to handle disasters.

scholarly journals Performance analysis for similarity data fusion model for enabling time series indexing in internet of things applications

2021 ◽  
Vol 7 ◽  
pp. e500
Author(s):  
Mina Younan ◽  
Essam H. Houssein ◽  
Mohamed Elhoseny ◽  
Abd El-mageid Ali
Keyword(s):  
Time Series ◽  
Performance Analysis ◽  
Internet Of Things ◽  
Real Time ◽  
The Internet ◽  
Fusion Model ◽  
Time Data ◽  
Iot Applications ◽  
Real Time Data ◽  
Smart Things

The Internet of Things (IoT) has penetrating all things and objects around us giving them the ability to interact with the Internet, i.e., things become Smart Things (SThs). As a result, SThs produce massive real-time data (i.e., big IoT data). Smartness of IoT applications bases mainly on services such as automatic control, events handling, and decision making. Consumers of the IoT services are not only human users, but also SThs. Consequently, the potential of IoT applications relies on supporting services such as searching, retrieving, mining, analyzing, and sharing real-time data. For enhancing search service in the IoT, our previous work presents a promising solution, called Cluster Representative (ClRe), for indexing similar SThs in IoT applications. ClRe algorithms could reduce similar indexing by O(K − 1), where K is number of Time Series (TS) in a cluster. Multiple extensions for ClRe algorithms were presented in another work for enhancing accuracy of indexed data. In this theme, this paper studies performance analysis of ClRe algorithms, proposes two novel execution methods: (a) Linear execution (LE) and (b) Pair-merge execution (PME), and studies sorting impact on TS execution for enhancing similarity rate for some ClRe extensions. The proposed execution methods are evaluated with real examples and proved using Szeged-weather dataset on ClRe 3.0 and its extensions; where they produce representatives with higher similarities compared to the other extensions. Evaluation results indicate that PME could improve performance of ClRe 3.0 by = 20.5%, ClRe 3.1 by = 17.7%, and ClRe 3.2 by = 6.4% in average.

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