scholarly journals An Affordable Fast Early Warning System for Edge Computing in Assembly Line

2018 ◽  
Vol 9 (1) ◽  
pp. 84 ◽  
Author(s):  
Muhammad Syafrudin ◽  
Norma Fitriyani ◽  
Ganjar Alfian ◽  
Jongtae Rhee
Keyword(s):  
Decision Making ◽  
Early Warning ◽  
Early Warning System ◽  
Assembly Line ◽  
Warning System ◽  
Edge Computing ◽  
Environmental Data ◽  
Proposed Model ◽  
Smart Factories ◽  
Abnormal Events

Maintaining product quality is essential for smart factories, hence detecting abnormal events in assembly line is important for timely decision-making. This study proposes an affordable fast early warning system based on edge computing to detect abnormal events during assembly line. The proposed model obtains environmental data from various sensors including gyroscopes, accelerometers, temperature, humidity, ambient light, and air quality. The fault model is installed close to the facilities, so abnormal events can be timely detected. Several performance evaluations are conducted to obtain the optimal scenario for utilizing edge devices to improve data processing and analysis speed, and the final proposed model provides the highest accuracy in terms of detecting abnormal events compared to other classification models. The proposed model was tested over four months of operation in a Korean automobile parts factory, and provided significant benefits from monitoring assembly line, as well as classifying abnormal events. The model helped improve decision-making by reducing or preventing unexpected losses due to abnormal events.

scholarly journals Three-Phase-Based Approach to Develop a River Health Prediction and Early Warning System to Guide River Management

2019 ◽  
Vol 9 (19) ◽  
pp. 4163
Author(s):  
Yongming Chen ◽  
Jihong Xia ◽  
Wangwei Cai ◽  
Zhilin Sun ◽  
Chuanbing Dou
Keyword(s):  
Decision Making ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
River System ◽  
Phase Iii ◽  
Health Index ◽  
River Health ◽  
Phase Approach ◽  
Three Phase

To effectively manage a river system, systematic tracking and diagnosing the change and risks of a river system are essentially required to efficiently conserve or restore its conditions. Hence, this study focuses on how to integrate current status assessment, trend prediction, and cause diagnosis in river health to guide early warning decision-making in river protection and management. This study has presented a three-phase approach by coupling spatial with nonspatial information in a highly systematic and reliable way, and an early warning system has been designed. In phase I, the current health status is assessed and nowcasted by using the order degree of each indicator. In phase II, health predictors, including the single perspective-based health index (HI) (e.g., water quality index (WQI) and index of biotic integrity (IBI)) and multi-perspective-based health index, have been forecasted under normal conditions or emerging conditions using predictive models. In phase III, key causal factors threatening the river health have been identified to enable early notification and to address unexpected events before occurrence. Although different modeling methods can be used in each phase to demonstrate this concept, we tested the model of partial least square regression (PLSR) associated with time series. Additionally, the three-phase approach has been integrated with geographic information system (GIS) and a decision support system (DSS) to develop a river health prediction and early warning system (RHP-EWS), an automatic prediction and decision-making tool. This tool was implemented to deal with the landing of typhoon “Maria” in 2018 into the Shanxi River watershed in China. Because of the timely responses and decisions, the drinking water supply was not influenced. However, the models should be extended to other river systems for testing and improvement at different temporal or spatial scales.

scholarly journals The Early Warning System and policymaking in the European Union

2020 ◽  
Vol 21 (3) ◽  
pp. 451-473 ◽  
Author(s):  
Philippe van Gruisen ◽  
Martijn Huysmans
Keyword(s):  
Decision Making ◽  
European Union ◽  
European Commission ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
The European Union ◽  
Relevant Aspect ◽  
Yellow Card ◽  
National Parliaments

Does the Early Warning System alert the European Commission about the prospects of passing new policy? We present a model of European Union policymaking in which the Early Warning System plays an important signalling role. In our model, the Commission uses signals from the Early Warning System to update its belief about governments’ voting strategies in the Council. The Commission may then anticipate difficult negotiations by withdrawing its proposal early. We find empirical evidence for our theory: (1) reasoned opinions submitted by national parliaments strongly predict opposition from their governments and (2) the Commission is more likely to withdraw proposals that receive reasoned opinions, even in the absence of a yellow card. Our results run counter to the dominant view in the literature that the Early Warning System is not a very relevant aspect of EU decision-making. Instead, reasoned opinions constitute a clear signal that negotiations are more likely to fail.

scholarly journals ANNs-Based Early Warning System for Indonesian Islamic Banks

2018 ◽  
Vol 20 (3) ◽  
pp. 325-342 ◽  
Author(s):  
Saiful Anwar ◽  
A.M Hasan Ali
Keyword(s):  
Financial Performance ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Financial Conditions ◽  
Proposed Model ◽  
Selection Of Variables ◽  
Sample Data ◽  
Out Of Sample ◽  
Macroeconomic Indicators

This research proposes a development of Early Warning System (EWS) model towards the financial performance of Islamic bank using financial ratios and macroeconomic indicators. The result of this paper is ready-to-use algorithm for the issue that needs to be solved shortly using machine learning technique which is not widely applied in Islamic banking. The research was conducted in three stages using Artificial Neural Networks (ANNs) technique: the selection of variables that significantly affect financial performance, developing an algorithm as a predictor and testing the predictor algorithm using out of sample data. Finally, the research concludes that the proposed model results in 100% accuracy for predicting Islamic bank’s financial conditions for the next two consecutive months.

scholarly journals Development of an Integrated Decision-Making Method for Effective Flood Early Warning System

2014 ◽  
Vol 9 (1) ◽  
pp. 55-68 ◽  
Author(s):  
Mamoru Miyamoto ◽  
◽  
Rabindra Osti ◽  
Toshio Okazumi ◽  
Keyword(s):  
Decision Making ◽  
Early Warning ◽  
Early Warning System ◽  
Fuzzy Ahp ◽  
Warning System ◽  
Flood Management ◽  
Flood Warning ◽  
Road Map ◽  
Integrated Decision Making ◽  
National Road

Floods in Bangladesh are often so catastrophic that they inflict substantial damage to the nation’s agriculture-based economy. To reduce this vulnerability, it is imperative to establish an effective flood early warning system across the country. There are too many urgent and complex issues about early flood warning activities in Bangladesh, however, and flood management is relatively complex, with several types of authorities currently involved in the effort. It is therefore necessary for stakeholders to create a National Road Map that offers future directions toward flood risk management. Issues prioritized by quantitative ranking in the implementation of an effective flood early warning must be identified on the National Road Map. In order to comprehensively prioritize listed interventions that are issues requiring improvement, two types of questionnaire were conducted. Next, multi-criteria analysis (MCA) and the analytic hierarchy process (AHP) strength, weakness, opportunity and threat (SWOT) were applied to survey results derived from pair-wise comparison, and both types of results were combined. Interventions with the highest priority in each cascade were identified based on quantitative importance. To ensure consistency among stakeholders, a fuzzy AHP was applied to each cascade. As a result, the most important and urgent interventions that contributed to creating a National Road Map were identified by integrated decision-making and new quantitative decision-making was shown by integrating MCA and AHP-SWOT.

A Managerial Early Warning System at a Smart Factory: An Intuitive Decision-making Perspective

2018 ◽  
Vol 35 (4) ◽  
pp. 406-416 ◽  
Author(s):  
Tine Bertoncel ◽  
Ivan Erenda ◽  
Mirjana Pejić Bach ◽  
Vasja Roblek ◽  
Maja Meško
Keyword(s):  
Decision Making ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Smart Factory ◽  
Intuitive Decision Making

scholarly journals Assessment of flood induced by heavy rainfall using advanced methodologies, as a premise for an integrated flood early warning system

2019 ◽  
Author(s):  
Ελισσάβετ Φελώνη
Keyword(s):  
Decision Making ◽  
Early Warning ◽  
Early Warning System ◽  
Heavy Rainfall ◽  
Warning System ◽  
Multi Criteria Decision Making

Η διδακτορική διατριβή (Δ.Δ.) με τίτλο: «Αξιολόγηση των ισχυρών βροχοπτώσεων που προκαλούν πλημμύρες με χρήση νέων τεχνολογιών, ως προοίμιο για ένα ολοκληρωμένο σύστημα έγκαιρης προειδοποίησης – Η περίπτωση της Αττικής» έχει ως αντικείμενο την εκτίμηση και ανάλυση των πλημμυρογόνων επεισοδίων βροχής αλλά και των πλημμυρών καθαυτών, αξιοποιώντας πρωτότυπα σύνολα δεδομένων, νέες τεχνολογίες και μεθοδολογίες. Η συνολική μεθοδολογία που αναπτύχθηκε εφαρμόστηκε στην Περιφέρεια Αττικής για την περίοδο 2005 – 2016, λαμβάνοντας υπόψη το σύνολο των πλημμυρικών γεγονότων στο ηπειρωτικό τμήμα της Περιφέρειας. Η χρήση των νέων τεχνολογιών και ιδιαίτερα των δυνατοτήτων των Συστημάτων Γεωγραφικών Πληροφοριακών (GIS) έχει μεγάλη σημασία σε ολόκληρη την ανάλυση, καθώς πρόκειται κυρίως για ένα γεωχωρικό πρόβλημα που προκαλείται εν μέρει από τους αποκαλούμενους στη Δ.Δ. «στατικούς» παράγοντες. Επίσης, είναι ένα πρόβλημα λήψης αποφάσεων πολλαπλών κριτηρίων, έτσι τα οφέλη από την εφαρμογή των μεθόδων πολυκριτηριακής ανάλυσης (Multi - Criteria Decision Making, “MCDM“) είναι αναμφισβήτητα καθοριστικά σε διάφορα στάδια της Δ.Δ. και ιδιαίτερα στον καθορισμό των ευάλωτων σε πλημμύρες περιοχών – παράμετρος που λαμβάνεται υπόψη κατά την οριοθέτηση 30 υποπεριοχών για τις οποίες πραγματοποιείται λεπτομερέστερη ανάλυση αναφορικά με ένα υποσύνολο παραγόντων. Εκτός των στατικών, διερευνήθηκαν και άλλοι παράγοντες που χαρακτηρίζονται ως «δυναμικοί», επειδή διαφοροποιούνται σε επίπεδο επεισοδίου βροχής. Οι παράγοντες αυτοί σχετίζονται με τις επικρατούσες υδρολογικές συνθήκες, την συνοπτική κατάσταση της ατμόσφαιρας και το γενικότερο υδρομετεωρολογικό πλαίσιο τις ημέρες των πλημμυρών. Οι εν λόγω παράγοντες υπολογίστηκαν και διερευνήθηκαν, ως ένας τρόπος να αξιολογηθούν τα χαρακτηριστικά των βροχοπτώσεων (π.χ., συνολικό ύψος, ένταση και τύπος βροχής, καιρικές συνθήκες κλπ.) που δυνητικά οδηγούν σε πλημμυρογένεση και που, σύμφωνα με την ίδια ανάλυση, αποδεικνύεται πως ορισμένοι εξ’ αυτών είναι καθοριστικής σημασίας για την πρόκληση πλημμύρας στην περιοχή. Ειδικότερα, ανάμεσα στους στατικούς παράγοντες η κλίση του και η ποσοστιαία αδιαπερατότητα των επιφανειών κρίνονται ως πιο καθοριστικοί παράγοντες. Επίσης, για ένα επιλεγμένο case study αξιολογήθηκε και ο παράγων «τρωτότητα κατασκευών» μέσω της αξιολόγησης επιμέρους χαρακτηριστικών για 252 ιδιοκτησίες που καταγράφηκαν ως πλημμυρικά συμβάντα κατά το επεισόδιο του Οκτωβρίου 2014. Αναφορικά με τους δυναμικούς παράγοντες, σε ποσοστό 55-70% οι πλημμύρες στην Αττική συνδέονται με κατακρήμνιση τύπου “convective“, το οποίο είναι σύμφωνο με τη διεθνή βιβλιογραφία για τη Μεσόγειο. Ο καθορισμός του τύπου της κατακρήμνισης βασίστηκε σε μια μεθοδολογία ταξινόμησης που επίσης αναπτύχθηκε και εφαρμόστηκε στο πλαίσιο της Δ.Δ. Ακόμα, τα πιο σημαντικά πλημμυρικά επεισόδια συνδέονται με την ύπαρξη ενός βαρομετρικού χαμηλού το οποίο ισχυροποιείται και βαθαίνει στα δυτικά της Αττικής, χωρίς ωστόσο να μπορεί να καθοριστεί ένα σαφές και ενιαίο μοτίβο για τις υπό εξέταση ατμοσφαιρικές παραμέτρους, γεγονός που πέρα από την ανάλυση ανά επεισόδιο, διερευνήθηκε σε εποχιακό επίπεδο και ανάλογα με τον τύπο κατακρήμνισης. Απεναντίας, η σε υψηλή χωρική ανάλυση (για τις 30 υποπεριοχές) συσχέτιση της μέγιστης έντασης βροχής (για διάφορες διάρκειες) με την εκδήλωση ή μη πλημμυρικών συμβάντων κατέδειξε τη δυνατότητα καθορισμού ενός σαφούς άνω ορίου εκδήλωσης πλημμύρας κατόπιν αφαίρεσης τυχόν εξωκείμενων τιμών. Η ισχυρή σύνδεση του εν λόγω παράγοντα με την πρόκληση πλημμυρών στην περιοχή παρέχει τη δυνατότητα σχεδιασμού ενός εργαλείου έγκαιρης προειδοποίησης για τον κίνδυνο πλημμύρας. Στο πλαίσιο της Δ.Δ. για το συγκεκριμένο εργαλείο εισάγεται ο όρος “F - EWT” (Flood- Early Warning Tool), το οποίο σχεδιάζεται για τις 30 υποπεριοχές και αξιολογείται για πραγματικά επεισόδια βροχής, όπου και ενδεικτικά παρουσιάζονται τα αποτελέσματα για την πλημμύρα του Οκτωβρίου 2014.

scholarly journals Wildfire early warning system based on wireless sensors and unmanned aerial vehicle

2019 ◽  
Vol 7 (1) ◽  
pp. 76-91 ◽  
Author(s):  
Songsheng Li
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Early Warning ◽  
Early Warning System ◽  
State Of The Art ◽  
Effective Means ◽  
Warning System ◽  
Environmental Data ◽  
Loss Of Life ◽  
Aerial Vehicle ◽  
Exchange Data

Wildfires erupt annually around the world causing serious loss of life and property damage. Despite the rapid progress of science and technology, there are no effective means to forecast wildfires. Various wildfire monitoring systems are deployed in different countries, most depend on photos or videos to identify features of wildfire after the first outbreak, while the delay of confirmation varies with technology. An autonomous forest wildfire early warning system is presented in this paper, which employs a state-of-the-art unmanned aerial vehicle (UAV) to fly around a forest regularly according to established routes and strict procedures, to collect environmental data from sensors installed on trees, to monitor and predict wildfire, then provide early warning before eruption if a danger emerges. Bluetooth Low Energy (BLE) is employed to exchange data between UAV and the host of sensors. The collected monitoring data, such as temperature and humidity, is effective to reflect the real condition of the forest, which could result in early warning of wildfires. The application of this system in the environment will enhance the ability of wildfire prediction for the community.

scholarly journals Assessing the electronic Bedside Paediatric Early Warning System: A simulation study on decision-making and usability

2020 ◽  
Vol 133 ◽  
pp. 103969
Author(s):  
Jessica N. Tomasi ◽  
Megan V. Hamilton ◽  
Mark Fan ◽  
Sonia J. Pinkney ◽  
Kristen L. Middaugh ◽  
...  
Keyword(s):  
Decision Making ◽  
Simulation Study ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
System A
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