scholarly journals Providing Fault Detection from Sensor Data in Complex Machines That Build the Smart City

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 586
Author(s):  
Alberto Gascón ◽  
Roberto Casas ◽  
David Buldain ◽  
Álvaro Marco
Keyword(s):  
Fault Detection ◽  
Smart City ◽  
Predictive Maintenance ◽  
Sensor Data ◽  
Climate Control ◽  
Sensors And Actuators ◽  
Limited Memory ◽  
Processing Power ◽  
Great Relevance ◽  
Network Good

Household appliances, climate control machines, vehicles, elevators, cash counting machines, etc., are complex machines with key contributions to the smart city. Those devices have limited memory and processing power, but they are not just actuators; they embed tens of sensors and actuators managed by several microcontrollers and microprocessors communicated by control buses. On the other hand, predictive maintenance and the capability of identifying failures to avoid greater damage of machines is becoming a topic of great relevance in Industry 4.0, and the large amount of data to be processed is a concern. This article proposes a layered methodology to enable complex machines with automatic fault detection or predictive maintenance. It presents a layered structure to perform the collection, filtering and extraction of indicators, along with their processing. The aim is to reduce the amount of data to work with, and to optimize them by generating indicators that concentrate the information provided by data. To test its applicability, a prototype of a cash counting machine has been used. With this prototype, different failure cases have been simulated by introducing defective elements. After the extraction of the indicators, using the Kullback–Liebler divergence, it has been possible to visualize the differences between the data associated with normal and failure operation. Subsequently, using a neural network, good results have been obtained, being able to correctly classify the failure in 90% of the cases. The result of this application demonstrates the proper functioning of the proposed approach in complex machines.

scholarly journals Shared Models and Open Infrastructures for the smart City Internet of Things based on the Semantic Web

2019 ◽  
Author(s):  
Mouad Banane ◽  
Abdessalam Belangour
Keyword(s):  
Semantic Web ◽  
Smart City ◽  
Ad Hoc ◽  
Smart Cities ◽  
Coordination Mechanism ◽  
Sensor Data ◽  
Proof Of Concept ◽  
Sensors And Actuators ◽  
Competition Control ◽  
The City

Contemporary cities face many challenges: energy, ecological, demographic or economic. To answer this, technological means are implemented in cities through the use of sensors and actuators. These cities are said to be smart. Currently, smart cities are operated by actors who share neither their sensor data nor access to their actuators. This situation is called vertical: each operator deploys its own sensors and actuators and has its own IT infrastructure hosting its applications. This leads to infrastructure redundancy and ad-hoc applications to oversee and control an area of the city. A trend is to move towards a so-called horizontal situation via the use of an open and shared mediation platform. Sensor data and access to the actuators are shared within this type of platform, allowing their sharing between the different actors. The costs of infrastructure and development are then reduced. This work is part of such a context of horizontalization, within an open and shared platform, in which we propose: 1) a layer of abstraction for control and supervision of the city, 2) a competition control mechanism handling conflict cases based on the RDF (Resource Description Framework) semantic Web standard, 3) a coordination mechanism promoting the reuse of actuators using ontology, 4) an implementation of our work by a proof of concept. The abstraction we propose is based on models from reactive systems. They aim to be generic and represent the invariant of the smart city: the physical elements. They allow applications to control and supervise the city. To facilitate the development of applications we standardize the interface of our models. Since these applications may have real-time constraints, especially those that have control objectives, we propose to take advantage of the distributed architecture of this type of platform. Given the sharing of the actuators, we have identified that conflicts can arise between applications. We propose a mechanism of competition control to deal with these cases of conflicts. We have also identified that a coordination mechanism must be offered to applications wishing to perform atomic control operations. Such a mechanism promotes the reuse of the actuators present in the city. Finally, we implemented our proposals around a proof of concept, including several use cases, to demonstrate our work.

scholarly journals Electronic Textiles

Encyclopedia ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 115-130
Author(s):  
Guido Ehrmann ◽  
Andrea Ehrmann
Keyword(s):  
Power Supply ◽  
Sensor Data ◽  
Electronic Textiles ◽  
Sensors And Actuators ◽  
External Communication ◽  
Data Processor ◽  
Temperature Strain

Electronic textiles belong to the broader range of smart (or “intelligent”) textiles. Their “smartness” is enabled by embedded or added electronics and allows the sensing of defined parameters of their environment as well as actuating according to these sensor data. For this purpose, different sensors (e.g., temperature, strain, light sensors) and actuators (e.g., LEDs or mechanical actuators) are embedded and connected with a power supply, a data processor, and internal/external communication.

scholarly journals A Data-Based Fault-Detection Model for Wireless Sensor Networks

2019 ◽  
Vol 11 (21) ◽  
pp. 6171 ◽  
Author(s):  
Jangsik Bae ◽  
Meonghun Lee ◽  
Changsun Shin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fault Detection ◽  
Data Transmission ◽  
Sensor Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sensors And Actuators ◽  
Detection Model ◽  
Management Platform

With the expansion of smart agriculture, wireless sensor networks are being increasingly applied. These networks collect environmental information, such as temperature, humidity, and CO2 rates. However, if a faulty sensor node operates continuously in the network, unnecessary data transmission adversely impacts the network. Accordingly, a data-based fault-detection algorithm was implemented in this study to analyze data of sensor nodes and determine faults, to prevent the corresponding nodes from transmitting data; thus, minimizing damage to the network. A cloud-based “farm as a service” optimized for smart farms was implemented as an example, and resource management of sensors and actuators was provided using the oneM2M common platform. The effectiveness of the proposed fault-detection model was verified on an integrated management platform based on the Internet of Things by collecting and analyzing data. The results confirm that when a faulty sensor node is not separated from the network, unnecessary data transmission of other sensor nodes occurs due to continuous abnormal data transmission; thus, increasing energy consumption and reducing the network lifetime.

Monitoring the Smart City Sensor Data Using Thingsboard and Node-Red

2021 ◽  
Author(s):  
Elham Okhovat ◽  
Michael Bauer
Keyword(s):  
Smart City ◽  
Sensor Data

Practice Report “Smart Disaster Management” — Combining Smart City Data and Citizen Participation to Increase Disaster Resilience

i-com ◽  
2021 ◽  
Vol 20 (2) ◽  
pp. 177-193
Author(s):  
Daniel Wessel ◽  
Julien Holtz ◽  
Florian König
Keyword(s):  
Citizen Participation ◽  
Smart City ◽  
Development Process ◽  
Smart Cities ◽  
Government Support ◽  
Sensor Data ◽  
Specific Information ◽  
Mutual Support ◽  
The Everyday

Abstract Smart cities have a huge potential to increase the everyday efficiency of cities, but also to increase preparation and resilience in case of natural disasters. Especially for disasters which are somewhat predicable like floods, sensor data can be used to provide citizens with up-to-date, personalized and location-specific information (street or even house level resolution). This information allows citizens to better prepare to avert water damage to their property, reduce the needed government support, and — by connecting citizens locally — improve mutual support among neighbors. But how can a smart city application be designed that is both usable and able to function during disaster conditions? Which smart city information can be used? How can the likelihood of mutual, local support be increased? In this practice report, we present the human-centered development process of an app to use Smart City data to better prepare citizens for floods and improve their mutual support during disasters as a case study to answer these questions.

Fault detection - Diagnosis and predictive maintenance

1986 ◽  
Author(s):  
Andre Rault ◽  
Chrysostome Baskiotis
Keyword(s):  
Fault Detection ◽  
Predictive Maintenance
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