IoT-based system for communication and coordination of football robot team

2017 ◽  
Vol 27 (2) ◽  
pp. 162-181 ◽  
Author(s):  
Zhuming Bi ◽  
Guoping Wang ◽  
Li Da Xu ◽  
Matt Thompson ◽  
Raihan Mir ◽  
...  
Keyword(s):  
Decision Making ◽  
Information System ◽  
Sensor Networks ◽  
Real Time ◽  
System Level ◽  
Time Data ◽  
Content Type ◽  
Iot Applications ◽  
Real Time Data ◽  
Communication And Coordination

Purpose The purpose of this paper is to develop an information system which is based on the Internet of things (IoT) and used to support the communication and coordination in a cooperative robot team. Design/methodology/approach The architecture of the IoT applications for decision-making activities in a complex system is elaborated, the focus lies on the effective implementation of system interactions at the device-level. A case study is provided to verify system performances. Findings The IoT concept has been introduced in an information system of a football robot team to support the coordination among team players. Various sensors are used to collect data from IoT, and data are processed for the controls of robotic players to achieve the better performance at the system level. The field test has shown the feasibility and effectiveness. Research limitations/implications To investigate how IoT can be utilized in an information system for making complex decisions effectively, the authors use the decision-support system for a football robot team to illustrate the approaches in developing data acquisition infrastructure, processing and utilizing real-time data for the communication and coordination of robot players in a dynamic competing environment. While the presented work has shown the feasibility of an IoT-based information system, more work are needed to integrate advanced sensors within the IoT and develop more intelligent algorithms to replace manually remote control for the operations of robot players. Practical implications The proposed system is specifically for a football robot team; however, the associated approaches are applicable to any decentralized system for developing an information system to support IoT-based communication and coordination within the system in the real-time mode. Originality/value The exploration of IoT applications is still at its early stage, existing relevant work is mostly limited to the development of system architecture, sensor networks, and communication protocols. In this paper, the methods on how to use massive real-time data for decision-making of a decentralized team have been investigated, and the proposed system has its theoretical significance to developing other decentralized wireless sensor networks and decision-making systems.

scholarly journals The Importance of Implementing Cyber Physical Systems to Acquire Real-Time Data and Indicators

J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 147-153
Author(s):  
Paula Morella ◽  
María Pilar Lambán ◽  
Jesús Antonio Royo ◽  
Juan Carlos Sánchez
Keyword(s):  
Decision Making ◽  
Data Acquisition ◽  
Real Time ◽  
Failure Detection ◽  
Cyber Physical Systems ◽  
Future Research ◽  
Time Data ◽  
Physical Systems ◽  
The Real ◽  
Real Time Data

Among the new trends in technology that have emerged through the Industry 4.0, Cyber Physical Systems (CPS) and Internet of Things (IoT) are crucial for the real-time data acquisition. This data acquisition, together with its transformation in valuable information, are indispensable for the development of real-time indicators. Moreover, real-time indicators provide companies with a competitive advantage over the competition since they enhance the calculus and speed up the decision-making and failure detection. Our research highlights the advantages of real-time data acquisition for supply chains, developing indicators that would be impossible to achieve with traditional systems, improving the accuracy of the existing ones and enhancing the real-time decision-making. Moreover, it brings out the importance of integrating technologies 4.0 in industry, in this case, CPS and IoT, and establishes the main points for a future research agenda of this topic.

Customer behavior analysis using real-time data processing

2019 ◽  
Vol 31 (1) ◽  
pp. 265-290 ◽  
Author(s):  
Ganjar Alfian ◽  
Muhammad Fazal Ijaz ◽  
Muhammad Syafrudin ◽  
M. Alex Syaekhoni ◽  
Norma Latif Fitriyani ◽  
...  
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Association Rule ◽  
Customer Behavior ◽  
Time Data ◽  
Content Type ◽  
The Real ◽  
Real Time Data ◽  
Real Time Data Processing ◽  
Big Data Technology

PurposeThe purpose of this paper is to propose customer behavior analysis based on real-time data processing and association rule for digital signage-based online store (DSOS). The real-time data processing based on big data technology (such as NoSQL MongoDB and Apache Kafka) is utilized to handle the vast amount of customer behavior data.Design/methodology/approachIn order to extract customer behavior patterns, customers’ browsing history and transactional data from digital signage (DS) could be used as the input for decision making. First, the authors developed a DSOS and installed it in different locations, so that customers could have the experience of browsing and buying a product. Second, the real-time data processing system gathered customers’ browsing history and transaction data as it occurred. In addition, the authors utilized the association rule to extract useful information from customer behavior, so it may be used by the managers to efficiently enhance the service quality.FindingsFirst, as the number of customers and DS increases, the proposed system was capable of processing a gigantic amount of input data conveniently. Second, the data set showed that as the number of visit and shopping duration increases, the chance of products being purchased also increased. Third, by combining purchasing and browsing data from customers, the association rules from the frequent transaction pattern were achieved. Thus, the products will have a high possibility to be purchased if they are used as recommendations.Research limitations/implicationsThis research empirically supports the theory of association rule that frequent patterns, correlations or causal relationship found in various kinds of databases. The scope of the present study is limited to DSOS, although the findings can be interpreted and generalized in a global business scenario.Practical implicationsThe proposed system is expected to help management in taking decisions such as improving the layout of the DS and providing better product suggestions to the customer.Social implicationsThe proposed system may be utilized to promote green products to the customer, having a positive impact on sustainability.Originality/valueThe key novelty of the present study lies in system development based on big data technology to handle the enormous amounts of data as well as analyzing the customer behavior in real time in the DSOS. The real-time data processing based on big data technology (such as NoSQL MongoDB and Apache Kafka) is used to handle the vast amount of customer behavior data. In addition, the present study proposed association rule to extract useful information from customer behavior. These results can be used for promotion as well as relevant product recommendations to DSOS customers. Besides in today’s changing retail environment, analyzing the customer behavior in real time in DSOS helps to attract and retain customers more efficiently and effectively, and retailers can get a competitive advantage over their competitors.

Development of an Intelligent Patrol Routing System Using GIS and Computer Simulations

2011 ◽  
pp. 339-351 ◽  
Author(s):  
Joseph Szakas ◽  
Christian Trefftz ◽  
Raul Ramirez ◽  
Eric Jefferis
Keyword(s):  
Information System ◽  
Real Time ◽  
Data Sets ◽  
Time Data ◽  
Map Algebra ◽  
Positioning Systems ◽  
Global Positioning ◽  
Real Time Data ◽  
Patrol Routing ◽  
Patrol Strategies

Patrolling in a nonrandom, but focused manner is an important activity in law enforcement. The use of geographic information systems, the emerging real-time data sets (spatial and nonspatial) and the ability via global positioning systems to identify locations of patrol units provide the environment to discuss the concept and requirements of an intelligent patrol routing system. This intelligent patrol routing system will combine available data utilizing Map Algebra and a data structure known as a Voronoi diagram to create a real-time updatable raster surface over the patrolling area to identify destination locations and routes for all patrol units. This information system will allow all patrol units to function “in concert” under a coordinated plan, and make good use of limited patrolling resources, and provide the means of evaluating current patrol strategies. This chapter discusses the algorithmic foundation, implications, requirements, and simulation of a GIS based intelligent patrol routing system.

Cassandra-based data repository design for food supply chain traceability

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sandeep Kumar Singh ◽  
Mamata Jenamani
Keyword(s):  
Supply Chain ◽  
Real Time ◽  
Radio Frequency Identification ◽  
Query Language ◽  
Data Repository ◽  
Time Data ◽  
Content Type ◽  
The Real ◽  
Traceability System ◽  
Real Time Data

Purpose The purpose of this paper is to design a supply chain database schema for Cassandra to store real-time data generated by Radio Frequency IDentification technology in a traceability system. Design/methodology/approach The real-time data generated in such traceability systems are of high frequency and volume, making it difficult to handle by traditional relational database technologies. To overcome this difficulty, a NoSQL database repository based on Casandra is proposed. The efficacy of the proposed schema is compared with two such databases, document-based MongoDB and column family-based Cassandra, which are suitable for storing traceability data. Findings The proposed Cassandra-based data repository outperforms the traditional Structured Query Language-based and MongoDB system from the literature in terms of concurrent reading, and works at par with respect to writing and updating of tracing queries. Originality/value The proposed schema is able to store the real-time data generated in a supply chain with low latency. To test the performance of the Cassandra-based data repository, a test-bed is designed in the lab and supply chain operations of Indian Public Distribution System are simulated to generate data.

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