Searching for Logical Patterns in Multi-sensor Data from the Industrial Internet

2016 ◽  
pp. 217-233
Author(s):  
Mohit Yadav ◽  
Ehtesham Hassan ◽  
Gautam Shroff ◽  
Puneet Agarwal ◽  
Ashwin Srinivasan
Keyword(s):  
Sensor Data ◽  
Industrial Internet

scholarly journals Advances in Future Internet and the Industrial Internet of Things

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 244 ◽  
Author(s):  
Jong Park
Keyword(s):  
Internet Of Things ◽  
Communication Networks ◽  
Future Internet ◽  
Resource Provisioning ◽  
Sensor Data ◽  
Third Wave ◽  
Industrial Internet Of Things ◽  
Privacy And Security ◽  
Industrial Internet ◽  
Use Of Internet

After the emergence of the Internet and mobile communication networks, the IoT has been considered as the third wave of information technology. The Industrial Internet of Things (IIoT) is the use of Internet of Things (IoT) technologies in manufacturing. IIoT incorporates machine learning and big data technology, sensor data, and machine-to-machine (M2M) communications that have existed in industrial areas for years. In the future, people and objects will be connected at any time, any place, with anything and anyone and will utilize any network and services. IIoT is creating a new world in which people and businesses can manage their assets in more informed ways and can make more opportune and better-informed decisions. Many advanced IIoT and 5G technologies have been successfully applied in everyday life, but there are still many practical problems tackled by traditional methods which are generally difficult to experimentally solve in the advanced Industrial Internet of Things. Therefore, in this special issue, we accepted five articles in three different dimensions: communication networks, optimized resource provisioning and data forwarding, privacy and security.

scholarly journals Visibility of resources and assets in the shipyard through industrial internet of things

2021 ◽  
Vol 11 (2) ◽  
pp. 88-101
Author(s):  
Ibrahim Cil ◽  
Fahri Arisoy ◽  
Hilal Kilinc
Keyword(s):  
Internet Of Things ◽  
Transformation Process ◽  
Digital Transformation ◽  
Sensor Data ◽  
Cyber Physical System ◽  
Industrial Internet Of Things ◽  
Use Of Data ◽  
Industrial Internet ◽  
Industrial Iot ◽  
Other Information

Industrial Internet of Things is becoming one of the fundamental technologies with the potential to be widely used in shipyards as in other industries to increase information visibility. This article aims to analyze how to develop an industrial IoT-enabled system that provides visibility and tracking of assets at SEDEF Shipyard, which is in the digital transformation process. The research made use of data from previous studies and by using content analysis, the findings were discussed. Industrial IoT enables the collection and analysis of data for more informed decisions.  Based on the findings, sensor data in the shipyard are transmitted to the cloud via connected networks. These data are analysed and combined with other information and presented to the stakeholders. Industrial IoT enables this data flow and monitors processes remotely and gives the ability to quickly change plans as needed. Keywords: Shipyard, Industrial Internet of Things, Cyber-Physical System, Visibility, Assets tracking;        

scholarly journals Towards Integrated Digital Twins for Industrial Products: Case Study on an Overhead Crane

2021 ◽  
Vol 11 (2) ◽  
pp. 683
Author(s):  
Juuso Autiosalo ◽  
Riku Ala-Laurinaho ◽  
Joel Mattila ◽  
Miika Valtonen ◽  
Valtteri Peltoranta ◽  
...  
Keyword(s):  
System Integration ◽  
Sensor Data ◽  
Overhead Crane ◽  
Application Development ◽  
Multiple Systems ◽  
Digital Twin ◽  
Industrial Companies ◽  
Digital Twins ◽  
Industrial Internet ◽  
Application Programming

Industrial Internet of Things practitioners are adopting the concept of digital twins at an accelerating pace. The features of digital twins range from simulation and analysis to real-time sensor data and system integration. Implementation examples of modeling-oriented twins are becoming commonplace in academic literature, but information management-focused twins that combine multiple systems are scarce. This study presents, analyzes, and draws recommendations from building a multi-component digital twin as an industry-university collaboration project and related smaller works. The objective of the studied project was to create a prototype implementation of an industrial digital twin for an overhead crane called “Ilmatar”, serving machine designers and maintainers in their daily tasks. Additionally, related cases focus on enhancing operation. This paper describes two tools, three frameworks, and eight proof-of-concept prototypes related to digital twin development. The experiences show that good-quality Application Programming Interfaces (APIs) are significant enablers for the development of digital twins. Hence, we recommend that traditional industrial companies start building their API portfolios. The experiences in digital twin application development led to the discovery of a novel API-based business network framework that helps organize digital twin data supply chains.

scholarly journals A Collaborative Augmented Reality Application for Training and Assistance during Shipbuilding Assembly Processes

Proceedings ◽  
2020 ◽  
Vol 54 (1) ◽  
pp. 4
Author(s):  
Aida Vidal-Balea ◽  
Oscar Blanco-Novoa ◽  
Paula Fraga-Lamas ◽  
Miguel Vilar-Montesinos ◽  
Tiago M. Fernández-Caramés
Keyword(s):  
Augmented Reality ◽  
User Interfaces ◽  
Sensor Data ◽  
3D Objects ◽  
Physical Measurements ◽  
Industrial Internet ◽  
Multiple Devices ◽  
Collaborative Augmented Reality ◽  
Microsoft Hololens ◽  
To Receive

This paper presents the development of a novel Microsoft HoloLens collaborative application that allows shipyard operators to interact with a virtual clutch during its assembly in a real Turbine workshop. Such an Augmented Reality (AR) experience acts as a virtual guide while assembling different parts of a ship. In particular, the proposed application allows operators to position the clutch on a real environment and interact with it. The application also provides information about the documentation of each part of the clutch, showing its blueprints and physical measurements. The proposed AR application enables collaborative AR experiences, allowing users to visualize the same content and animations at the same time and interact simultaneously with 3D objects from multiple devices. Furthermore, the application is integrated with an Industrial Internet of Things (IIoT) framework, resulting on an AR-IIoT application that is able to receive and display real-time sensor data on information panels, as well as to trigger actions through actuators by making use of virtual user interfaces.

scholarly journals Process-Driven and Flow-Based Processing of Industrial Sensor Data

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5245
Author(s):  
Klaus Kammerer ◽  
Rüdiger Pryss ◽  
Burkhard Hoppenstedt ◽  
Kevin Sommer ◽  
Manfred Reichert
Keyword(s):  
Sensor Data ◽  
Technical Solution ◽  
Manufacturing Companies ◽  
Industrial Internet Of Things ◽  
Capture Process ◽  
Processing Pipeline ◽  
Digital Services ◽  
Industrial Internet ◽  
Sensor Processing ◽  
Recorded Data

For machine manufacturing companies, besides the production of high quality and reliable machines, requirements have emerged to maintain machine-related aspects through digital services. The development of such services in the field of the Industrial Internet of Things (IIoT) is dealing with solutions such as effective condition monitoring and predictive maintenance. However, appropriate data sources are needed on which digital services can be technically based. As many powerful and cheap sensors have been introduced over the last years, their integration into complex machines is promising for developing digital services for various scenarios. It is apparent that for components handling recorded data of these sensors they must usually deal with large amounts of data. In particular, the labeling of raw sensor data must be furthered by a technical solution. To deal with these data handling challenges in a generic way, a sensor processing pipeline (SPP) was developed, which provides effective methods to capture, process, store, and visualize raw sensor data based on a processing chain. Based on the example of a machine manufacturing company, the SPP approach is presented in this work. For the company involved, the approach has revealed promising results.

scholarly journals A Dynamic Taint Tracking Optimized Fuzz Testing Method based on Multi-modal Sensor Data Fusion

2020 ◽  
Author(s):  
Qianmu Li ◽  
Shunmei Meng ◽  
Hanrui Zhang ◽  
Yaozong Liu ◽  
Haiyuan Shen ◽  
...  
Keyword(s):  
Test Methods ◽  
Sensor Data ◽  
Test Cases ◽  
Industrial Control ◽  
Code Coverage ◽  
Fuzz Testing ◽  
Internet Control ◽  
Industrial Internet ◽  
Control Terminal ◽  
Taint Tracking

Abstract The safety of Industrial Internet Control Systems has been a hotspot in the information security. To meet needs of communication, a large variety of proprietary protocols have emerged in the field of industrial control. The protocol field is often trusted in the implementation of industrial control terminal code. If attackers modify the data of these fields using the protocol defect, the operation of the program can be controlled and the entire system will be affected. To cope with such security threats, academia and industry generally adopt fuzzy test methods. However, the current industrial control protocol fuzzy test methods generally have low code coverage, where unified description models are missing and test cases are not targeted. A method of fuzzification processing combined with dynamic multi-modal sensor communication data is proposed. To track the program execution, the dynamic pollution analysis is used to search for the input fields that affect the execution of the conditional branch, and capture the dependencies between the conditional branches to guide the grammar generation of test cases, which can increase the chances of executing deep code. The experimental results show that the proposed method improves the validity and code coverage of test cases to a certain extent, and greatly increases the probability of anomaly detection in the protocol implementation

Recurrence Behavior Statistics of Blast Furnace Gas Sensor Data in Industrial Internet of Things

2020 ◽  
Vol 7 (6) ◽  
pp. 5666-5676
Author(s):  
Yingqi Li ◽  
Di Cai ◽  
Jialin Wang ◽  
Xiaochuan Sun ◽  
Zhigang Li ◽  
...  
Keyword(s):  
Blast Furnace ◽  
Internet Of Things ◽  
Gas Sensor ◽  
Sensor Data ◽  
Industrial Internet Of Things ◽  
Blast Furnace Gas ◽  
Industrial Internet ◽  
Recurrence Behavior

scholarly journals A Dynamic Taint Tracking Optimized Fuzz Testing Method based on Multi-modal Sensor Data Fusion

2020 ◽  
Author(s):  
Qianmu Li ◽  
Shunmei Meng ◽  
Hanrui Zhang ◽  
Yaozong Liu ◽  
Haiyuan Shen ◽  
...  
Keyword(s):  
Test Methods ◽  
Sensor Data ◽  
Test Cases ◽  
Industrial Control ◽  
Code Coverage ◽  
Fuzz Testing ◽  
Internet Control ◽  
Industrial Internet ◽  
Control Terminal ◽  
Taint Tracking

Abstract The safety of Industrial Internet Control Systems has been a hotspot in the information security. To meet needs of communication, a large variety of proprietary protocols have emerged in the field of industrial control. The protocol field is often trusted in the implementation of industrial control terminal code. If attackers modify the data of these fields using the protocol defect, the operation of the program can be controlled and the entire system will be affected. To cope with such security threats, academia and industry generally adopt fuzz test methods. However, the current industrial control protocol fuzz test methods generally have low code coverage, where unified description models are missing and test cases are not targeted. A method of fuzzification processing combined with dynamic multi-modal sensor communication data is proposed. To track the program execution, the dynamic pollution analysis is used to search for the input fields that affect the execution of the conditional branch, and capture the dependencies between the conditional branches to guide the grammar generation of test cases, which can increase the chances of executing deep code. The experimental results show that the proposed method improves the validity and code coverage of test cases to a certain extent, and greatly increases the probability of anomaly detection in the protocol implementation.

scholarly journals A Dynamic Taint Tracking Optimized Fuzz Testing Method based on Multi-modal Sensor Data Fusion

2020 ◽  
Author(s):  
Qianmu Li ◽  
Shunmei Meng ◽  
Hanrui Zhang ◽  
Yaozong Liu ◽  
Haiyuan Shen ◽  
...  
Keyword(s):  
Test Methods ◽  
Sensor Data ◽  
Test Cases ◽  
Industrial Control ◽  
Code Coverage ◽  
Fuzz Testing ◽  
Internet Control ◽  
Industrial Internet ◽  
Control Terminal ◽  
Taint Tracking

Abstract The safety of Industrial Internet Control Systems has been a hotspot in the information security. To meet needs of communication, a large variety of proprietary protocols have emerged in the field of industrial control. The protocol field is often trusted in the implementation of industrial control terminal code. If attackers modify the data of these fields using the protocol defect, the operation of the program can be controlled and the entire system will be affected. To cope with such security threats, academia and industry generally adopt fuzzy test methods. However, the current industrial control protocol fuzzy test methods generally have low code coverage, where unified description models are missing and test cases are not targeted. A method of fuzzification processing combined with dynamic multi-modal sensor communication data is proposed. To track the program execution, the dynamic pollution analysis is used to search for the input fields that affect the execution of the conditional branch, and capture the dependencies between the conditional branches to guide the grammar generation of test cases, which can increase the chances of executing deep code. The experimental results show that the proposed method improves the validity and code coverage of test cases to a certain extent, and greatly increases the probability of anomaly detection in the protocol implementation.

Sign in / Sign up

Export Citation Format

Share Document