scholarly journals BIG DATA ON DIGITAL LOGISTICS IN SUPPLY CHAIN RISK PERSPECTIVE

2018 ◽  
Vol 2 (1) ◽  
pp. 21-30
Author(s):  
Resista Vikaliana

In Industry 4.0, digital transformation moves quickly, flexibly and efficiently. Logistics and supply chains have transformed into web-based. Internet of things (IoT) and Big Data are important in the decision making process.  The importance of big data doesn’t revolve around how much data you have, but what you do with it. In addition to the opportunities to use big data, there are possible risks that must be anticipated. The wide range of data that can be obtained, so that in practice key risk indicators will act as an early warning system for the entity. Key risk indicators and their parameters.

2021 ◽  
Author(s):  
Gaurab Sagar Dawadi

<p>The Early Warning System (EWS)  is recognized as a crucial mechanism for disaster risk reduction. Despite advances in technologies, the biggest shortcoming of EWS is that risk information is still failing to reach the people at risk in developing countries like Nepal and India. This presentation is based on the qualitative analysis of 90 interviews conducted for my Ph.D. thesis, in the Kosi River basin, across the Nepal-India border. Annually the Kosi River and its tributaries cause widespread flooding and inundation in Nepal and India. Recently, significant advancements have occurred in the sector of risk communication for Flood-EWS in Nepal and India. Government institutions use mobile text messages, web-based Apps, flood bulletins, and other measures to inform people about the flood. Despite the efforts, significant challenges were observed in the information outreach, especially to the women and vulnerable people living in the study area. Challenges were also identified in understanding the received text messages by flood vulnerable people, and spatially relating the information about river depth for their evacuation decision.  Recommendations were made for inclusive and people-centered EWS based on Impact based forecasting as well as on awareness-raising activities through mobile applications.</p>


2019 ◽  
Vol 17 (9) ◽  
pp. 818-822 ◽  
Author(s):  
Flaminia Pantano ◽  
Silvia Graziano ◽  
Roberta Pacifici ◽  
Francesco Paolo Busardò ◽  
Simona Pichini

In the last few years, a wide range of new psychoactive substances (NPS) have been produced and marketed to elude the controlled substance lists. These molecules enter the traditional illegal and web market with poor knowledge about their toxicity, mechanism of action, metabolism, abuse potential so that they are directly tested by the consumers. This perspective highlights the main issues connected with NPS: the celerity they enter and leave the market once included in the banning laws to be substituted by new legal analogues; the unavailability of analytical screening tests and certified standards to perform toxicological analyses; the time lag between NPS identification and inclusion in the controlled substances lists. Finally, the authors take a snapshot of the commitment of the Italian Early Warning System in highlighting the recent seizures of NPS as well as the distribution of NPS related intoxication and deaths as an example of what is happening in the European countries and internationally.


2014 ◽  
Vol 16 (5) ◽  
pp. 1041-1049 ◽  
Author(s):  
Scott Bainbridge ◽  
Ray Berkelmans

In response to coral bleaching in the Torres Strait in 2009–10 an ocean monitoring program was established. This included a bleaching early warning system that uses real time data, climatologies and Bayesian models to deliver risk indicators linked to management outcomes.


Author(s):  
N. Trushkina ◽  
◽  
H. Dzwigol ◽  
O. Serhieieva ◽  
Yu. Shkrygun ◽  
...  

The transition to a digital economy is becoming a key driver of GDP growth. This is due not only to the effect obtained from the automation of existing processes, but also from the introduction of new, breakthrough business models and technologies, including digital platforms, digital ecosystems, in-depth analytics of big data, Industry 4.0, Logistics 4.0. At the same time, digital transformation is seen as a radical change in the complex of business processes, from product development to customer service, as well as the introduction of modern digital technologies in the organization of business processes in enterprises. The purpose of the article is to analysis the features and trends of organizing logistics activities in the context of digital transformation of business processes; research of the main prerequisites for the formation of the Logistics 4.0 concept; determination of priority directions for its further development in the context of Industry 4.0. Based on the generalization of scientific approaches, the definition of the concept of "Logistics 4.0" has been clarified, which means the modern paradigm of managing logistic (material, financial, information, transport) flows and organizing a complex of logistics activities (purchase and delivery of material resources, warehousing, production, stock formation, recycling of industrial waste, customer service, transportation and sale of finished products) using breakthrough digital technologies and information systems. The priority areas of organizing the logistics activities of enterprises using digital technologies include the following: multichannel logistics; logistics marketplaces; rethinking the use of packaging; mass personalization; Silver Economy (new services for older clients and new opportunities for older workers); sustainable logistics; sharing economy; multi-supply; customer experience; smart containerization; big data analytics; augmented and virtual reality; cloud service applications and APIs; Internet of Things; robotics and automation; new generation wireless communication; blockchain; Artificial Intelligence; unmanned aerial vehicles or "drones"; 3D printing; unmanned vehicles; quantum computing; supergrid logistics; space logistics; the use of digital platforms that unite customers and transport and logistics companies (the parties can enter into digital contracts, exchange transport booking requests and electronic documents, control the delivery of goods in real time). All this can help to reduce costs by optimizing procurement; decrease in personnel costs and decrease in labour costs as a result of automation; reduction of errors in logistics; optimization of the supply process; efficient warehouse management; forecasting shipments; creation of optimal routes; operational planning of loads and control of delivery times; ensuring product delivery on time, improving customer loyalty; optimal interaction with customers on the "last mile".


Author(s):  
C. Y. Yang ◽  
J. Y. Liu ◽  
S. Huang

Abstract. Because most schools have been using traditional methods to manage students, there is a lack of effective monitoring of students' behavioral problems. In order to solve this problem, this paper analyses the characteristics of big data in University campus, adopts K-Means algorithm, a traditional clustering analysis algorithm, and proposes an early warning system of College Students' behavior based on Internet of Things and big data environment under the mainstream Hadoop open source platform. The system excavates and analyses the potential connections in the massive data of these campuses, studies the characteristics of students' behavior, analyses the law of students' behavior, and clusters the categories of students' behavior. It can provide students, colleges, schools and logistics management departments with multi-dimensional behavior analysis and prediction, early warning and safety control of students' behavior, realize the informatization of students' management means, improve the scientific level of students' education management, and promote the construction of intelligent digital campus.


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