Remote sensing based on time variance control in configurable area partitioning

Abstract. In this paper a sensor data fusion approach for characteristics field monitoring, based on time variance control model, is proposed. Distributed sensing and remote processing are the basic features of the employed architecture. In fact, in order to obtain meaningful information about the temporal and spatial variations, which characterize the field levels of some characteristics (electromagnetic, air pollution, seismic, etc), a distributed network of wireless and mobile smart-sensors has been designed.Starting from the partitioned configuration of a monitored geographic areas, this model allows to take into account the different levels of degradation over time in the sensors' performances associated with the different geographic partitions, progressively increasing the severity of the control. To this end, through the introduction of a reliability curve, a revised traditional control chart for variables is proposed.The proposed approach, further constituting an element of the scientific debate, aims to be a useful operational tool for professionals and managers employed in the environment control.

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Die Entgrenzung von Arbeit und die Transformation raumbezogener Orientierungen – Eine Annäherung in der Region Halle/Leipzig

Geographica Helvetica ◽

10.5194/gh-68-105-2013 ◽

2013 ◽

Vol 68 (2) ◽

pp. 105-116 ◽

Cited By ~ 1

Author(s):

G. Montanari ◽

K. Wiest ◽

S. Wörmer

Keyword(s):

Everyday Life ◽

Household Survey ◽

Time Geography ◽

Residential Areas ◽

Scientific Debate ◽

Reflexive Modernity ◽

Temporal And Spatial ◽

Depth Interviews ◽

Different Levels ◽

Work And Life

Abstract. Major trends in society like flexibilisation, blurring of boundaries between life spheres and subjectification of labour come along with new requirements in individual's everyday life. In the scientific debate it has in contrast hardly been discussed how these trends affect different levels of society beyond social strata like the creative class. Referring to the concepts of reflexive modernity and time-geography the focus of this article is on temporal and spatial aspects of societal change and its effects on everyday life. Based on in-depth interviews and a household survey carried out in different residential areas in the region of Halle-Leipzig the paper points out how blurred borders between "work'' and "life'' affect individuals' space-time activities between new opportunities and new constraints. Here an inner-city neighbourhood and a community in the urban sprawl between Halle and Leipzig are under consideration to highlight different strategies to deal with weakening associations between activities, place and time emerging in different settlement structures.

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Temporal and Spatial Nearest Neighbor Values Based Missing Data Imputation in Wireless Sensor Networks

Sensors ◽

10.3390/s21051782 ◽

2021 ◽

Vol 21 (5) ◽

pp. 1782

Author(s):

Yulong Deng ◽

Chong Han ◽

Jian Guo ◽

Lijuan Sun

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Missing Data ◽

Nearest Neighbor ◽

Sensor Data ◽

Wireless Sensor ◽

Data Imputation ◽

Missing Data Imputation ◽

Temporal And Spatial ◽

Two Parameters

Data missing is a common problem in wireless sensor networks. Currently, to ensure the performance of data processing, making imputation for the missing data is the most common method before getting into sensor data analysis. In this paper, the temporal and spatial nearest neighbor values-based missing data imputation (TSNN), a new imputation based on the temporal and spatial nearest neighbor values has been presented. First, four nearest neighbor values have been defined from the perspective of space and time dimensions as well as the geometrical and data distances, which are the bases of the algorithm that help to exploit the correlations among sensor data on the nodes with the regression tool. Next, the algorithm has been elaborated as well as two parameters, the best number of neighbors and spatial–temporal coefficient. Finally, the algorithm has been tested on an indoor and an outdoor wireless sensor network, and the result shows that TSNN is able to improve the accuracy of imputation and increase the number of cases that can be imputed effectively.

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A numerical study of synchronization in the process of biochemical substance exchange in a diffusively coupled ring of cells

Open Physics ◽

10.2478/s11534-013-0221-5 ◽

2013 ◽

Vol 11 (4) ◽

Cited By ~ 1

Author(s):

Dragutin Mihailović ◽

Igor Balaž ◽

Ilija Arsenić

Keyword(s):

Kolmogorov Complexity ◽

Numerical Study ◽

Logistic Map ◽

Sample Entropy ◽

Cell System ◽

Negotiation Process ◽

Cell Affinity ◽

Basic Features ◽

Biochemical Substance ◽

Different Levels

AbstractIn this paper we numerically investigate a model of a diffusively coupled ring of cells. To model the dynamics of individual cells we propose a map with cell affinity, which is a generalization of the logistic map. First, the basic features of a one-cell system are studied in terms of the Lyapunov exponent, Kolmogorov complexity and Sample Entropy. Second, the notion of observational heterarchy, which is a perpetual negotiation process between different levels of the description of a phenomenon, is reviewed. After these preliminaries, we study how the active coupling induced by the consideration of the observational heterarchy modifies the synchronization property of the model with N=100 cells. It is shown numerically that the active coupling enhances synchronization of biochemical substance exchange in several different conditions of cell affinity.

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Databases for Specialized Audiences: An Exploration of Online Access to the Nontextual Features of Greek New Testament Manuscripts

Advances in Archaeological Practice ◽

10.1017/aap.2018.54 ◽

2019 ◽

Vol 7 (1) ◽

pp. 97-105 ◽

Cited By ~ 1

Author(s):

Marina Toumpouri

Keyword(s):

New Testament ◽

Medieval Manuscripts ◽

Preservation Condition ◽

Different Types ◽

Greek New Testament ◽

Temporal And Spatial ◽

Object Of Study ◽

Physical Features ◽

Interface Organization ◽

Different Levels

AbstractSince the beginning of the century, the digitization of medieval manuscripts has been a major concern of institutions in the possession of such material. This has led to the massive production of digital surrogates for online display. Preservation condition and temporal and spatial limitations are no longer restrictions for accessing these objects, making them easily available to a potentially larger public than before. The databases created for hosting the surrogates are designed for different categories of audience, with various standards in mind and different levels of technical sophistication. Although primarily accessed for the texts they bear, the digital surrogates of manuscripts are also the object of study of a specialized group of users interested in their physical features. This review will discuss whether databases that comprise digital surrogates of Greek New Testament manuscripts built by different types of institutions are efficient in addressing the needs of this admittedly small audience. I examine questions of content, interface, organization, and rationales behind the choices of their creators.

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Multi-Sensor Fusion Approach for Improving Map-Based Indoor Pedestrian Localization

Sensors ◽

10.3390/s19173786 ◽

2019 ◽

Vol 19 (17) ◽

pp. 3786 ◽

Cited By ~ 4

Author(s):

Huang ◽

Hsieh ◽

Liu ◽

Cheng ◽

Hsu ◽

...

Keyword(s):

Sensor Fusion ◽

Navigation System ◽

Inertial Sensor ◽

Indoor Navigation ◽

Sensor Data ◽

Interior Space ◽

Localization Accuracy ◽

Light Sensor ◽

Indoor Navigation System ◽

Fusion Approach

The interior space of large-scale buildings, such as hospitals, with a variety of departments, is so complicated that people may easily lose their way while visiting. Difficulties in wayfinding can cause stress, anxiety, frustration and safety issues to patients and families. An indoor navigation system including route planning and localization is utilized to guide people from one place to another. The localization of moving subjects is a critical-function component in an indoor navigation system. Pedestrian dead reckoning (PDR) is a technology that is widely employed for localization due to the advantage of being independent of infrastructure. To improve the accuracy of the localization system, combining different technologies is one of the solutions. In this study, a multi-sensor fusion approach is proposed to improve the accuracy of the PDR system by utilizing a light sensor, Bluetooth and map information. These simple mechanisms are applied to deal with the issue of accumulative error by identifying edge and sub-edge information from both Bluetooth and the light sensor. Overall, the accumulative error of the proposed multi-sensor fusion approach is below 65 cm in different cases of light arrangement. Compared to inertial sensor-based PDR system, the proposed multi-sensor fusion approach can improve 90% of the localization accuracy in an environment with an appropriate density of ceiling-mounted lamps. The results demonstrate that the proposed approach can improve the localization accuracy by utilizing multi-sensor data and fulfill the feasibility requirements of localization in an indoor navigation system.

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A Decision-Level Data Fusion Approach to Surface Roughness Prediction

Volume 1: Additive Manufacturing; Manufacturing Equipment and Systems; Bio and Sustainable Manufacturing ◽

10.1115/msec2019-2976 ◽

2019 ◽

Author(s):

Yupeng Wei ◽

Dazhong Wu ◽

Janis Terpenny

Keyword(s):

Surface Roughness ◽

Data Fusion ◽

Process Monitoring ◽

Predictive Models ◽

Sensor Data ◽

Fused Deposition ◽

Decision Level ◽

Level Data ◽

Fusion Approach

Abstract To improve the quality of additively manufactured parts, it is crucial to develop real-time process monitoring systems and data-driven predictive models. While various sensor- and image-based process monitoring methods have been developed to improve the quality of additively manufactured parts, very limited research has been conducted to predict surface roughness. To fill this gap, this paper presents a decision-level data fusion approach to predicting surface roughness in the fused deposition modeling (FDM) process. The predictive models are trained by the random forests method using multiple sensor signals. A decision-level data fusion method is introduced to integrate sensor data sources. Experimental results have shown that the decision-level data fusion approach can predict surface roughness in FDM with high accuracy.

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Automation for Water and Nitrogen Deficit Stress Detection in Soilless Tomato Crops Based on Spectral Indices

Horticulturae ◽

10.3390/horticulturae4040047 ◽

2018 ◽

Vol 4 (4) ◽

pp. 47 ◽

Cited By ~ 2

Author(s):

Angeliki Elvanidi ◽

Nikolaos Katsoulas ◽

Constantinos Kittas

Keyword(s):

Crop Production ◽

Control Strategies ◽

Classification Tree ◽

Management Strategies ◽

Total Sample ◽

Sensor Data ◽

Limiting Factors ◽

Tree Model ◽

Environment Control ◽

The Impact

Water and nitrogen deficit stress are some of the most important growth limiting factors in crop production. Several methods have been used to quantify the impact of water and nitrogen deficit stress on plant physiology. However, by performing machine learning with hyperspectral sensor data, crop physiology management systems are integrated into real artificial intelligence systems, providing richer recommendations and insights into implementing appropriate irrigation and environment control management strategies. In this study, the Classification Tree model was used to group complex hyperspectral datasets in order to provide remote visual results about plant water and nitrogen deficit stress. Soilless tomato crops are grown under varying water and nitrogen regimes. The model that we developed was trained using 75% of the total sample dataset, while the rest (25%) of the data were used to validate the model. The results showed that the combination of MSAVI, mrNDVI, and PRI had the potential to determine water and nitrogen deficit stress with 89.6% and 91.4% classification accuracy values for the training and testing samples, respectively. The results of the current study are promising for developing control strategies for sustainable greenhouse production.

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Predictive maintenance as an internet of things enabled business model: A taxonomy

Electronic Markets ◽

10.1007/s12525-020-00440-5 ◽

2020 ◽

Cited By ~ 1

Author(s):

Jens Passlick ◽

Sonja Dreyer ◽

Daniel Olivotti ◽

Lukas Grützner ◽

Dennis Eilers ◽

...

Keyword(s):

Cluster Analysis ◽

Internet Of Things ◽

Manufacturing Industry ◽

Business Models ◽

Predictive Maintenance ◽

Sensor Data ◽

Visualization Technique ◽

Hardware Development ◽

The Internet Of Things ◽

Different Levels

Abstract Predictive maintenance (PdM) is an important application of the Internet of Things (IoT) discussed in many companies, especially in the manufacturing industry. PdM uses data, usually sensor data, to optimize maintenance activities. We develop a taxonomy to classify PdM business models that enables a comparison and analysis of such models. We use our taxonomy to classify the business models of 113 companies. Based on this classification, we identify six archetypes using cluster analysis and discuss the results. The “hardware development”, “analytics provider”, and “all-in-one” archetypes are the most frequently represented in the study sample. For cluster analysis, we use a visualization technique that involves an autoencoder. The results of our analysis will help practitioners assess their own business models and those of other companies. Business models can be better differentiated by considering the different levels of IoT architecture, which is also an important implication for further research.

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Structural components of space as a component of logistic

MATEC Web of Conferences ◽

10.1051/matecconf/201823903003 ◽

2018 ◽

Vol 239 ◽

pp. 03003 ◽

Cited By ~ 2

Author(s):

Elena Koroleva ◽

Irina Makashina ◽

Evgeniya Filatova ◽

Sergei Sokolov

Keyword(s):

Transport Process ◽

Structural Components ◽

Freight Forwarding ◽

Basic Features ◽

Different Levels

In this article the author's interpretation of the concept of transport space is offered, its brief characteristic is given. The basic features of the transport space and evidence of the existence of its variable hierarchy that allows observe the transport space at different levels of specificity, are specified. It is shown that freight forwarding can be considered as one of the subspaces of the transport space. It is proved that one of the main requirements for the development of this component should be the requirement to implement the maximum possible information conductivity of all its elements and links, and, therefore, the maximum interest of all its participants. An important role in the study of the transport process has been formulated. The described technique displays all the iterative components of the transport aspect.

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