Key challenges and developments in non-targeted methods or systems to identify food adulteration

2021 ◽  
pp. 175-204
Author(s):  
Sara Erasmus ◽  
◽  
Saskia van Ruth ◽  
Keyword(s):  
Big Data Analysis ◽  
Food Fraud ◽  
Supply Chain Networks ◽  
Global Challenge ◽  
Technological Developments ◽  
Increased Sensitivity ◽  
Multiple Challenges ◽  
Analytical Tools ◽  
The Internet Of Things ◽  
Associated Data

Food fraud is an ongoing global challenge that is amplified by the complexity of supply chain networks and fraudsters becoming more innovative in the way they commit fraud. There is a great need for rapid analytical tools that offer broad product screening. Non-targeted methods provide an approach by which a food matrix can be analysed and screened for adulterations. While various developments exist for rapid non-targeted approaches, there are still multiple challenges to overcome. More work is required to validate, harmonise and standardise non-targeted methods and the associated data interpretations. Promising advances include novel technological developments with devices becoming smaller and portable with increased sensitivity. It is undoubtedly that fingerprinting approaches generate huge datasets that need to be stored and utilised as effectively as possible; creating new opportunities for Big data analysis and the Internet of Things – both addressing the need to convert data into insights to act upon.

Big Data Analytics Tools and Platform in Big Data Landscape

2018 ◽  
pp. 80-89
Author(s):  
Mohd Imran ◽  
Mohd Vasim Ahamad ◽  
Misbahul Haque ◽  
Mohd Shoaib
Keyword(s):  
Big Data ◽  
Comparative Analysis ◽  
Comparative Study ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Big Data Analysis ◽  
Apache Hadoop ◽  
Pros And Cons ◽  
The Comparative Study ◽  
Analytical Tools

The term big data analytics refers to mining and analyzing of the voluminous amount of data in big data by using various tools and platforms. Some of the popular tools are Apache Hadoop, Apache Spark, HBase, Storm, Grid Gain, HPCC, Casandra, Pig, Hive, and No SQL, etc. These tools are used depending on the parameter taken for big data analysis. So, we need a comparative analysis of such analytical tools to choose best and simpler way of analysis to gain more optimal throughput and efficient mining. This chapter contributes to a comparative study of big data analytics tools based on different aspects such as their functionality, pros, and cons based on characteristics that can be used to determine the best and most efficient among them. Through the comparative study, people are capable of using such tools in a more efficient way.

Industry 4.0 and the Internet of Things (IoT)

2020 ◽  
pp. 1-24
Author(s):  
Zelal Gültekin Kutlu
Keyword(s):  
Internet Of Things ◽  
Industry 4.0 ◽  
Information Technologies ◽  
Industrial Revolution ◽  
The Internet ◽  
Automation Systems ◽  
Technological Developments ◽  
Use Of The Internet ◽  
Internet Networks ◽  
The Internet Of Things

In this study, the periodical differences of industrial revolutions, which is one of the effects of technological developments in the industrial field, and the last stage of it are mentioned. With the latest industrial revolution called Industry 4.0, machines work in harmony with technology at every stage of industrial areas. This period, known as Industry 4.0 or the fourth industrial revolution, refers to the system in which the latest production technologies, automation systems, and the technologies that make up this system exchange data with each other. In addition to the information technologies and automation systems used in Industry 3.0, industrial production has gained a whole new dimension with the use of the internet. With internet networks, machines, operators, and robots now work in harmony. At this point, the concept of internet of objects becomes important. Therefore, another focus of the study is the concept of internet of objects. There are some assumptions about the uses, benefits, and future status of the internet of things.

Big Data Analytics Tools and Platform in Big Data Landscape

2022 ◽  
pp. 622-631
Author(s):  
Mohd Imran ◽  
Mohd Vasim Ahamad ◽  
Misbahul Haque ◽  
Mohd Shoaib
Keyword(s):  
Big Data ◽  
Comparative Analysis ◽  
Comparative Study ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Big Data Analysis ◽  
Apache Hadoop ◽  
Pros And Cons ◽  
The Comparative Study ◽  
Analytical Tools

The term big data analytics refers to mining and analyzing of the voluminous amount of data in big data by using various tools and platforms. Some of the popular tools are Apache Hadoop, Apache Spark, HBase, Storm, Grid Gain, HPCC, Casandra, Pig, Hive, and No SQL, etc. These tools are used depending on the parameter taken for big data analysis. So, we need a comparative analysis of such analytical tools to choose best and simpler way of analysis to gain more optimal throughput and efficient mining. This chapter contributes to a comparative study of big data analytics tools based on different aspects such as their functionality, pros, and cons based on characteristics that can be used to determine the best and most efficient among them. Through the comparative study, people are capable of using such tools in a more efficient way.

scholarly journals A Survey of Using Swarm Intelligence Algorithms in IoT

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1420 ◽  
Author(s):  
Weifeng Sun ◽  
Min Tang ◽  
Lijun Zhang ◽  
Zhiqiang Huo ◽  
Lei Shu
Keyword(s):  
Swarm Intelligence ◽  
Big Data Analysis ◽  
Wireless Sensor ◽  
Future Trends ◽  
Distribution Characteristics ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Wireless Telecommunications ◽  
Research Problems ◽  
The Internet Of Things

With the continuing advancements in technologies (such as machine to machine, wireless telecommunications, artificial intelligence, and big data analysis), the Internet of Things (IoT) aims to connect everything for information sharing and intelligent decision-making. Swarm intelligence (SI) provides the possibility of SI behavior through collaboration in individuals that have limited or no intelligence. Its potential parallelism and distribution characteristics can be used to realize global optimization and solve nonlinear complex problems. This paper reviews representative SI algorithms and summarizes their applications in the IoT. The main focus consists in the analysis of SI-enabled applications to wireless sensor network (WSN) and discussion of related research problems in the WSN. Also, we concluded SI-based applications in other IoT fields, such as SI in UAV-aided wireless network. Finally, possible research prospects and future trends are drawn.

The social library in three contexts: Programmes and perspectives

2015 ◽  
Vol 49 (3) ◽  
pp. 237-245 ◽  
Author(s):  
Kristian Nagel Delica ◽  
Hans Elbeshausen
Keyword(s):  
Public Libraries ◽  
Common Features ◽  
Institutional Knowledge ◽  
National Differences ◽  
The Social ◽  
Technological Developments ◽  
Multiple Challenges ◽  
The Uk

Across different national contexts public libraries have dealt, in diverse yet comparable ways, with the multiple challenges stemming from globalization, migration, marginalization and technological developments. This article argues, by way of dissecting three cases of library planning programmes which focused on centring libraries in their neighbourhoods, that we in recent decades witness the contours of a social library. Discussing experiences from initiatives in the UK, Canada and Denmark we, notwithstanding significant national differences, highlight common features – that libraries bring together already existing, but hitherto isolated institutional knowledge and competencies. We conclude by proposing a tentative typology of ‘the social library’.

scholarly journals IoT-Fog-Cloud system architecture for big data analysis and cybersecurity systems: a review of fog computing, the introduction to the Internet of Things audit

2020 ◽  
Author(s):  
D. R. Kolisnyk ◽  
◽  
K. S. Misevych ◽  
S. V. Kovalenko
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Internet Of Things ◽  
System Architecture ◽  
Fog Computing ◽  
Big Data Analysis ◽  
Future Research ◽  
The Internet ◽  
Security Issues ◽  
The Internet Of Things

The article considers the issues of system architecture IoT-Fog-Cloud, considers the interaction between the three levels of IoT, Fog and Cloud for the effective implementation of programs for big data analysis and cybersecurity. The article also discusses security issues, solutions and directions for future research in the field of the Internet of Things and nebulous computing.

scholarly journals IoT platforms for the Mining Industry: An Overview

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Paulina GACKOWIEC ◽  
Marta PODOBIŃSKA-STANIEC
Keyword(s):  
Internet Of Things ◽  
Predictive Analytics ◽  
Mining Industry ◽  
The Internet ◽  
Device Management ◽  
Computer Tools ◽  
Complex Processes ◽  
Use Of The Internet ◽  
Analytical Tools ◽  
The Internet Of Things

Industry 4.0 and the Internet of Things are now very common concepts as solutions that can revolutionize the industry. Constanttechnological progress increases the possibilities of using computer tools and solutions to support processes in industry and productionoptimization. The use of the Internet of Things is particularly important in complex processes in mining, enabling the extractionof valuable information from data. The integration of physical facilities in the enterprise enables the digitization of productionprocesses and the increase of efficiency and security.This article presents an overview of the selected internet of things platforms and analytical tools that can be used in industry, withparticular emphasis on the mining sector. It is pointed out, that the number of suppliers of IoT technologies and analytical toolsoffering advanced data analytics services for industry is significant and constantly evolving. The aim of the article is to evaluateselected IoT solutions based on the following criteria: offering predictive analytics, implemented artificial intelligence (AI) ormachine learning (ML) algorithms, a mining-oriented process approach, advanced data visualization, interoperability, real-timedata capture, remote device management and cloud-based technology. The review was prepared to provide knowledge about IoTvendors operating on the market, as well as to indicate the functionalities that are the most popular among solutions.

scholarly journals Information Security Terminal Architecture of Power Transportation Mobile Internet of Things Based on Big Data Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xianzhi Tang ◽  
Chunyan Ding
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Information Security ◽  
Internet Of Things ◽  
Power System ◽  
Big Data Analysis ◽  
The Internet ◽  
Mobile Information ◽  
Internet Of Things Technology ◽  
The Internet Of Things

The progress of the social economy and the rapid development of the power field have created more favorable conditions for the construction of my country’s power grid. In this network age, how to further realize the connection between the power system and the Internet of Things is the key content of many scholars’ research. In the Internet of Things environment, there have been many excellent results in the collection, storage, and management of electric power big data, but the problem of information security has not been completely solved. Based on big data analysis and Internet of Things technology, this paper studies the architecture design of power information security terminals. In view of the diverse types of power grid mobile information and the large amount of data, this paper designs a power transportation mobile information security management system structure, which improves the effective management of power data by the system through big data, smart sensors, and wireless communication technology. According to the experiment, the power information security terminal constructed in this paper can effectively reduce communication resources and save communication costs in the process of aggregating multidimensional data. In the user satisfaction survey, residents’ satisfaction with the convenience and safety of the intelligent power system is also as high as 9.312 and 9.233. On the whole, the application of big data and Internet of Things technology to the construction of power information security terminals can indeed improve the service efficiency of power companies under the premise of ensuring safety and allow users to have a better experience.

scholarly journals 4.0 For Agriculture

2020 ◽  
Vol 5 (3) ◽  
Author(s):  
Aylin Yılmaz ◽  
M. Atilla Arıcıoğlu ◽  
Nadiye Gülnar
Keyword(s):  
Industry 4.0 ◽  
Agricultural Sector ◽  
Agricultural Practices ◽  
Agricultural Field ◽  
Use Of Technology ◽  
Smart Farming ◽  
The World ◽  
Technological Developments ◽  
The Internet Of Things ◽  
Better Than

Recently, there was a struggle to control the volume of production and the volume of production between countries and regions in the world. Rather, western countries had a desire to attract investments in the east to their own countries and regions. This desire has led to the emergence of the Industry 4.0 phenomenon of the West, which is Germany. In other words, with this phenomenon, the industry is aimed to digitize production more and contribute to the issues of speed, efficiency and flexibility by providing digitalization in production. With these changes, Industry 4.0, was seen that the system was working better than it was and production was made cheaper than the system, when taking the muscle strength out of the system. While the positive contributions of Industry 4.0 have resonated with all sectors, it has also started to have an impact on the agricultural sector. Problems such as scarcity in the world, not using natural resources effectively and not using technology in the agricultural field, have caused the emergence of digitalization in the agricultural sector. "Agriculture 4.0", wich means making smart production with smart farming practices by using the concepts, information and technologies in the literature. In line with the possibilities and technological developments offered by Industry 4.0, it enables the sensors to be seen in all agricultural machines from the tractor to the crop tools and the communication of the machines in the entire production process by entering the internet of things into the agricultural sector. As a matter of fact, with the agriculture 4.0, the traditional agriculture paradigm has not been sufficient anymore and it contributes to sustainability, to be productive, to protect the rural texture, to protect the environmental quality and to provide accessible food by undergoing changes and agricultural practices. In the study, the problems experienced in the agricultural sector, the effects of Agriculture 4.0 on these problems and how they will benefit are discussed. The use of technology has given the system its name and agriculture has also taken its share in the developments. Accordingly, what are the practices of Agriculture 4.0 in the world and how their contributions are investigated.

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