Driver Attention Monitoring System using IBM Cloud

With online shopping and many logistic companies on the rise, a single accident can incur heavy loss to the supply chain department and not only disrupts the flow of the supply chain, but also causes injury to life and damage to property. These accidents occur primarily due to driving while feeling distracted or drowsy and it is paramount to monitor such behavior to avoid drastic outcomes in case of driving heavy duty vehicles. Therefore, it is natural for logistic companies to invest in securing their goods and ensuring that there is safe transportation of goods. The objective of our paper is to provide a novel solution to handle the aforementioned problems by monitoring the driver’s performance by analysing the facial features of the driver in real-time while storing the event-triggered data in the cloud and using the cloud services to send mobile alerts when the driver is drowsy or distracted via a mobile application in a cost effective and in an efficient manner.

Download Full-text

Traceable Air Baggage Handling System Based on RFID Tags in the Airport

Journal of theoretical and applied electronic commerce research ◽

10.3390/jtaer3010011 ◽

2008 ◽

Vol 3 (1) ◽

pp. 106-115 ◽

Cited By ~ 1

Author(s):

Ting Zhang ◽

Yuanxin Ouyang ◽

Yang He

Keyword(s):

Supply Chain ◽

Real Time ◽

Recognition Rate ◽

Cost Effective ◽

Object Identification ◽

Rfid Tags ◽

Handling System ◽

International Airport ◽

Management Efficiency ◽

Baggage Handling

The RFID is not only a feasible, novel, and cost-effective candidate for daily object identification but it is also considered as a significant tool to provide traceable visibility along different stages of the aviation supply chain. In the air baggage handing application, the RFID tags are used to enhance the ability for baggage tracking, dispatching and conveyance so as to improve the management efficiency and the users’ satisfaction. We surveyed current related work and introduce the IATA RP1740c protocol used for the standard to recognize the baggage tags. One distributed aviation baggage traceable application is designed based on the RFID networks. We describe the RFID-based baggage tracking experiment in the BCIA (Beijing Capital International Airport). In this experiment the tags are sealed in the printed baggage label and the RFID readers are fixed in the certain interested positions of the BHS in the Terminal 2. We measure the accurate recognition rate and monitor the baggage’s real-time situation on the monitor’s screen. Through the analysis of the measured results within two months we emphasize the advantage of the adoption of RFID tags in this high noisy BHS environment. The economical benefits achieved by the extensive deployment of RFID in the baggage handing system are also outlined.

Download Full-text

Modeling Fused Filament Fabrication using Artificial Neural Networks

Production Engineering ◽

10.1007/s11740-021-01020-y ◽

2021 ◽

Author(s):

Paul Oehlmann ◽

Paul Osswald ◽

Juan Camilo Blanco ◽

Martin Friedrich ◽

Dominik Rietzel ◽

...

Keyword(s):

Real Time ◽

Large Scale ◽

Cost Effective ◽

Print Quality ◽

Ann Model ◽

Production Environment ◽

Fused Filament Fabrication ◽

Artificial Neural ◽

Using Data ◽

Artificial Neural Network Ann

AbstractWith industries pushing towards digitalized production, adaption to expectations and increasing requirements for modern applications, has brought additive manufacturing (AM) to the forefront of Industry 4.0. In fact, AM is a main accelerator for digital production with its possibilities in structural design, such as topology optimization, production flexibility, customization, product development, to name a few. Fused Filament Fabrication (FFF) is a widespread and practical tool for rapid prototyping that also demonstrates the importance of AM technologies through its accessibility to the general public by creating cost effective desktop solutions. An increasing integration of systems in an intelligent production environment also enables the generation of large-scale data to be used for process monitoring and process control. Deep learning as a form of artificial intelligence (AI) and more specifically, a method of machine learning (ML) is ideal for handling big data. This study uses a trained artificial neural network (ANN) model as a digital shadow to predict the force within the nozzle of an FFF printer using filament speed and nozzle temperatures as input data. After the ANN model was tested using data from a theoretical model it was implemented to predict the behavior using real-time printer data. For this purpose, an FFF printer was equipped with sensors that collect real time printer data during the printing process. The ANN model reflected the kinematics of melting and flow predicted by models currently available for various speeds of printing. The model allows for a deeper understanding of the influencing process parameters which ultimately results in the determination of the optimum combination of process speed and print quality.

Download Full-text

Third Party Certification of Agri-Food Supply Chain Using Smart Contracts and Blockchain Tokens

Sensors ◽

10.3390/s21165307 ◽

2021 ◽

Vol 21 (16) ◽

pp. 5307

Author(s):

Ricardo Borges dos Santos ◽

Nunzio Marco Torrisi ◽

Rodrigo Palucci Pantoni

Keyword(s):

Supply Chain ◽

Mobile Application ◽

Consumer Behaviour ◽

Economic Incentives ◽

Third Party ◽

Smart Contracts ◽

Proof Of Concept ◽

Socially Responsible ◽

The Public ◽

Blockchain Technology

Every consumer’s buying decision at the supermarket influences food brands to make first party claims of sustainability and socially responsible farming methods on their agro-product labels. Fine wines are often subject to counterfeit along the supply chain to the consumer. This paper presents a method for efficient unrestricted publicity to third party certification (TPC) of plant agricultural products, starting at harvest, using smart contracts and blockchain tokens. The method is capable of providing economic incentives to the actors along the supply chain. A proof-of-concept using a modified Ethereum IGR token set of smart contracts using the ERC-1155 standard NFTs was deployed on the Rinkeby test net and evaluated. The main findings include (a) allowing immediate access to TPC by the public for any desired authority by using token smart contracts. (b) Food safety can be enhanced through TPC visible to consumers through mobile application and blockchain technology, thus reducing counterfeiting and green washing. (c) The framework is structured and maintained because participants obtain economical incentives thus leveraging it´s practical usage. In summary, this implementation of TPC broadcasting through tokens can improve transparency and sustainable conscientious consumer behaviour, thus enabling a more trustworthy supply chain transparency.

Download Full-text

Transformation of the Innovative and Sustainable Supply Chain with Upcoming Real-Time Fashion Systems

Sustainability ◽

10.3390/su13031081 ◽

2021 ◽

Vol 13 (3) ◽

pp. 1081

Author(s):

Yoon Kyung Lee

Keyword(s):

Supply Chain ◽

Real Time ◽

Computer Aided Design ◽

Production Systems ◽

Fashion Industry ◽

Sustainable Supply Chain ◽

Information Communication ◽

Manufacturing Planning ◽

Fashion Products ◽

Aided Design

Technologies that are ready-to-use and adaptable in real time to customers’ individual needs are influencing the supply chain of the future. This study proposes a supply chain framework for an innovative and sustainable real-time fashion system (RTFS) between enterprises, designers, and consumers in 3D clothing production systems, using information communication technology, artificial intelligence (AI), and virtual environments. In particular, the RTFS is targeted at customers actively involved in product purchasing, personalising, co-designing, and manufacturing planning. The fashion industry is oriented towards 3D services as a service model, owing to the automation and democratisation of product customisation and personalisation processes. Furthermore, AI offers referral services to prosumers or/and customers and companies, and proposes individual designs with perfect styles and measurements using new 3D computer aided design and AI-based product design technologies for fashion and design companies and customers. Consequently, 3D fashion products in the RTFS supply chain are entirely digital, saving time and money with sampling and tracking capabilities, secured, and trusted with personalised service delivery.

Download Full-text

Development of The Personnel Monitoring System Using Mobile Application and Real-Time Database During the COVID19 Pandemic

2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) ◽

10.1109/isriti51436.2020.9315377 ◽

2020 ◽

Author(s):

Muladi ◽

Aripriharta ◽

Ilham Ari Elbaith Zaeni ◽

Siti Sendari ◽

Abd. Kadir bin Mahamad ◽

...

Keyword(s):

Real Time ◽

Monitoring System ◽

Mobile Application ◽

Real Time Database

Download Full-text

Cost-Effective Real-Time Metabolic Profiling of Cancer Cell Lines for Plate-Based Assays

Chemosensors ◽

10.3390/chemosensors9060139 ◽

2021 ◽

Vol 9 (6) ◽

pp. 139

Author(s):

Wiktoria Blaszczak ◽

Zhengchu Tan ◽

Pawel Swietach

Keyword(s):

Real Time ◽

Cell Lines ◽

Acid Production ◽

Metabolic Regulation ◽

Cost Effective ◽

Culture Conditions ◽

Metabolic Inhibitors ◽

Metabolic Phenotype ◽

Ductal Adenocarcinoma ◽

Oxygen Utilization

A fundamental phenotype of cancer cells is their metabolic profile, which is routinely described in terms of glycolytic and respiratory rates. Various devices and protocols have been designed to quantify glycolysis and respiration from the rates of acid production and oxygen utilization, respectively, but many of these approaches have limitations, including concerns about their cost-ineffectiveness, inadequate normalization procedures, or short probing time-frames. As a result, many methods for measuring metabolism are incompatible with cell culture conditions, particularly in the context of high-throughput applications. Here, we present a simple plate-based approach for real-time measurements of acid production and oxygen depletion under typical culture conditions that enable metabolic monitoring for extended periods of time. Using this approach, it is possible to calculate metabolic fluxes and, uniquely, describe the system at steady-state. By controlling the conditions with respect to pH buffering, O2 diffusion, medium volume, and cell numbers, our workflow can accurately describe the metabolic phenotype of cells in terms of molar fluxes. This direct measure of glycolysis and respiration is conducive for between-runs and even between-laboratory comparisons. To illustrate the utility of this approach, we characterize the phenotype of pancreatic ductal adenocarcinoma cell lines and measure their response to a switch of metabolic substrate and the presence of metabolic inhibitors. In summary, the method can deliver a robust appraisal of metabolism in cell lines, with applications in drug screening and in quantitative studies of metabolic regulation.

Download Full-text

Cost-Effective Scraping and Processing of Real-time Traffic Data for Route Planning

2021 International Conference on Computer & Information Sciences (ICCOINS) ◽

10.1109/iccoins49721.2021.9497145 ◽

2021 ◽

Author(s):

Hong Le Tee ◽

Soung-Yue Liew ◽

Chee-Siang Wong ◽

Boon-Yaik Ooi

Keyword(s):

Real Time ◽

Route Planning ◽

Cost Effective ◽

Traffic Data ◽

Real Time Traffic

Download Full-text

Simple, cost-effective technique for portable digital eletrocorticography

Arquivos de Neuro-Psiquiatria ◽

10.1590/s0004-282x2000000300005 ◽

2000 ◽

Vol 58 (2B) ◽

pp. 424-427 ◽

Cited By ~ 1

Author(s):

PAULO R. M. DE BITTENCOURT ◽

MARCOS C. SANDMANN ◽

MARLUS S. MORO ◽

JOÃO C. DE ARAÚJO

Keyword(s):

Real Time ◽

Epilepsy Surgery ◽

Vascular Malformations ◽

Cost Effective ◽

New Method ◽

Cortical Lesions ◽

Effective Technique ◽

Seizure Disorders ◽

Operational Costs ◽

Cost Effective Technique

We revised 16 patients submitted to epilepsy surgery using a new method of digital, real-time, portable electrocorticography. Patients were operated upon over a period of 28 months. There were no complications. The exam was useful in 13 cases. The low installation and operational costs, the reliability and simplicity of the method, indicate it may be useful for defining the epileptogenic regions in a variety of circumnstances, including surgery for tumors, vascular malformations, and other cortical lesions associated with seizure disorders.

Download Full-text