Pub Date : 2017-06-01DOI: 10.1109/CIVEMSA.2017.7995333
Amy R. Wagoner, D. Schrader, E. Matson
Unmanned aerial vehicles (UAVs) are rapidly increasing in popularity. Despite attempts at regulation, stopping small, Class 1 (typically hobby-grade) UAVs from entering protected or sensitive airspace is an unsolved problem. Many companies and researchers offer a piece of a solution, but as of this writing, there is no publicly available, feasible, end-to-end solution. Ultimately, what is needed is a sensor-based system that autonomously detects, tracks, and neutralizes/disables an incoming UAV. However, such a system is currently not available, so as development toward that goal continues, a temporary solution is required. Augmenting the skill, dexterity, and processing power of human pilots with inexpensive cameras and computer vision algorithms can offer such a solution. The foundations of a framework for a system that uses computer vision to target and ultimately destroy a target in mid-air is introduced. The proposed solution utilizes a light-weight, inexpensive UAV with an on-board camera. The detection and tracking is performed in real-time on a companion computer mounted to the frame of the vehicle, with ROS as the primary communication infrastructure. Initial simulations provide insight into the feasibility of using computer vision with a monocular camera to offer reliable assistance to the pilot.
{"title":"Towards a vision-based targeting system for counter unmanned aerial systems (CUAS)","authors":"Amy R. Wagoner, D. Schrader, E. Matson","doi":"10.1109/CIVEMSA.2017.7995333","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2017.7995333","url":null,"abstract":"Unmanned aerial vehicles (UAVs) are rapidly increasing in popularity. Despite attempts at regulation, stopping small, Class 1 (typically hobby-grade) UAVs from entering protected or sensitive airspace is an unsolved problem. Many companies and researchers offer a piece of a solution, but as of this writing, there is no publicly available, feasible, end-to-end solution. Ultimately, what is needed is a sensor-based system that autonomously detects, tracks, and neutralizes/disables an incoming UAV. However, such a system is currently not available, so as development toward that goal continues, a temporary solution is required. Augmenting the skill, dexterity, and processing power of human pilots with inexpensive cameras and computer vision algorithms can offer such a solution. The foundations of a framework for a system that uses computer vision to target and ultimately destroy a target in mid-air is introduced. The proposed solution utilizes a light-weight, inexpensive UAV with an on-board camera. The detection and tracking is performed in real-time on a companion computer mounted to the frame of the vehicle, with ROS as the primary communication infrastructure. Initial simulations provide insight into the feasibility of using computer vision with a monocular camera to offer reliable assistance to the pilot.","PeriodicalId":123360,"journal":{"name":"2017 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116991301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.1109/civemsa.2017.7995338
O. Strauss
Digital image processing refers to the set of algorithms used to transform, filter, enhance, modify, analyze, distort, fuse, etc., digital images. Most of these algorithms are designed to mimic an underlying physical operation defined in the continuous illumination domain and formerly achieved via optical or electronic filters or through manipulations, including painting, cutting, moving or pasting of image patches. It also allows more sophisticated transformations (associated to more or less complex algorithms) which would be impossible to process by analog means. It may be quite hard to completely transpose an operation from the continuous to the discrete domain. Such a transposition usually relies on methods that ensure a kind of interplay between continuous and discrete domains. The interplay between the continuous and the discrete domain usually involves a convolution with a point spread function, when the measurement model is supposed to be linear, while the interplay between the discrete and the continuous domain is ensured by interpolation or more generally approximation methods, which also involve a convolution with a reconstruction kernel. Performing a precise identification of the point spread function of an imager is usually pretty challenging. Moreover, modeling the imaging process by a point spread function could be considered as an approximation of a more complex (and not shift-invariant) phenomenon (e.g. radial distortion or chromatic aberrations).
{"title":"Possibility theory in image processing","authors":"O. Strauss","doi":"10.1109/civemsa.2017.7995338","DOIUrl":"https://doi.org/10.1109/civemsa.2017.7995338","url":null,"abstract":"Digital image processing refers to the set of algorithms used to transform, filter, enhance, modify, analyze, distort, fuse, etc., digital images. Most of these algorithms are designed to mimic an underlying physical operation defined in the continuous illumination domain and formerly achieved via optical or electronic filters or through manipulations, including painting, cutting, moving or pasting of image patches. It also allows more sophisticated transformations (associated to more or less complex algorithms) which would be impossible to process by analog means. It may be quite hard to completely transpose an operation from the continuous to the discrete domain. Such a transposition usually relies on methods that ensure a kind of interplay between continuous and discrete domains. The interplay between the continuous and the discrete domain usually involves a convolution with a point spread function, when the measurement model is supposed to be linear, while the interplay between the discrete and the continuous domain is ensured by interpolation or more generally approximation methods, which also involve a convolution with a reconstruction kernel. Performing a precise identification of the point spread function of an imager is usually pretty challenging. Moreover, modeling the imaging process by a point spread function could be considered as an approximation of a more complex (and not shift-invariant) phenomenon (e.g. radial distortion or chromatic aberrations).","PeriodicalId":123360,"journal":{"name":"2017 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126259322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.1109/CIVEMSA.2017.7995295
Insaf Sassi, Alexia Gouin, J. Thiriet
Mobile networked robots are distributed systems controlled by a distant station i.e, the controller is implemented on a control station. The main mission of the mobile robot is reaching a target position starting from an initial one while receiving the instructions from the control station via a wireless network. The wireless network is characterized by a stochastic behavior and is sensitive to perturbations. The unreliability of wireless networks does not guarantee data transmission between system components (the robot and the station) which can cause system performance degradation. A distributed Bayesian Network (BN) was proposed in previous work to monitor and diagnose the system performance and to model causal uncertainties between failures. The developed BN is a modular Bayesian Network (MBN) which is composed of three Bayesian modules shared between the robot and the control station. In the case of system performance degradation because of a bad network state, the robot switches to embedded controller implemented on-board (autonomous behavior). The distributed diagnosis architecture must be updated and the diagnosis tool becomes embedded on the robot. A procedure of BNs assembly is described in this work in order to implement one monolithic BN on-board. The obtained monolithic BN is the result of combining two Bayesian modules from the modular Bayesian Network: the control and the operative Bayesian modules.
{"title":"Distributed to embedded Bayesian Network for diagnosis of a networked robot","authors":"Insaf Sassi, Alexia Gouin, J. Thiriet","doi":"10.1109/CIVEMSA.2017.7995295","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2017.7995295","url":null,"abstract":"Mobile networked robots are distributed systems controlled by a distant station i.e, the controller is implemented on a control station. The main mission of the mobile robot is reaching a target position starting from an initial one while receiving the instructions from the control station via a wireless network. The wireless network is characterized by a stochastic behavior and is sensitive to perturbations. The unreliability of wireless networks does not guarantee data transmission between system components (the robot and the station) which can cause system performance degradation. A distributed Bayesian Network (BN) was proposed in previous work to monitor and diagnose the system performance and to model causal uncertainties between failures. The developed BN is a modular Bayesian Network (MBN) which is composed of three Bayesian modules shared between the robot and the control station. In the case of system performance degradation because of a bad network state, the robot switches to embedded controller implemented on-board (autonomous behavior). The distributed diagnosis architecture must be updated and the diagnosis tool becomes embedded on the robot. A procedure of BNs assembly is described in this work in order to implement one monolithic BN on-board. The obtained monolithic BN is the result of combining two Bayesian modules from the modular Bayesian Network: the control and the operative Bayesian modules.","PeriodicalId":123360,"journal":{"name":"2017 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134210360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.1109/CIVEMSA.2017.7995304
Amir Hooshiar, M. Razban, N. Bandari, J. Dargahi
This study was aimed to prove the conceptual basis of a new sensing principle, capable of characterizing the viscoelastic properties of beating myocardial tissue. In this regard, a sensing principle based on the spontaneous contact between the beating cardiac wall and a force-displacement sensor was proposed. A multi-parameter, mass-spring mechanical model of myocardial tissue was proposed. A series of experiments, resembling the sensor function and the cardiac wall motion was setup. The mechanical response of the model subjected to the boundary condition from the experiments was simulated. The results of the simulation were analyzed against variation in the model parameters and the cardiac wall velocity. The model with the best fitting parameters was then subjected to higher cardiac wall velocity to predict the contact force. The model could fit the experimental results with up to 97.9% resemblance and could predict the contact force for with up to 95.1% similarity. The significant similarity of the simulated results with the experiments could prove the consistency of the proposed mechanism. Moreover, the fast and repeatable computations for the sensing principle enables this method to be a good candidate for integration into the cardiac robotic surgeries.
{"title":"Sensing principle for real-time characterization of viscoelasticity in the beating myocardial tissue","authors":"Amir Hooshiar, M. Razban, N. Bandari, J. Dargahi","doi":"10.1109/CIVEMSA.2017.7995304","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2017.7995304","url":null,"abstract":"This study was aimed to prove the conceptual basis of a new sensing principle, capable of characterizing the viscoelastic properties of beating myocardial tissue. In this regard, a sensing principle based on the spontaneous contact between the beating cardiac wall and a force-displacement sensor was proposed. A multi-parameter, mass-spring mechanical model of myocardial tissue was proposed. A series of experiments, resembling the sensor function and the cardiac wall motion was setup. The mechanical response of the model subjected to the boundary condition from the experiments was simulated. The results of the simulation were analyzed against variation in the model parameters and the cardiac wall velocity. The model with the best fitting parameters was then subjected to higher cardiac wall velocity to predict the contact force. The model could fit the experimental results with up to 97.9% resemblance and could predict the contact force for with up to 95.1% similarity. The significant similarity of the simulated results with the experiments could prove the consistency of the proposed mechanism. Moreover, the fast and repeatable computations for the sensing principle enables this method to be a good candidate for integration into the cardiac robotic surgeries.","PeriodicalId":123360,"journal":{"name":"2017 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132969291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.1109/CIVEMSA.2017.7995314
Cedric Deffo Sikounmo, S. Perrin, E. Benoit
This paper proposes a new contribution to manage uncertainty in the context of a situation recognition. It gives an application to the measurement of housing use situations. It extends a previous communication that proposes an ontological based model of situations. In this model, a situation is a set of entities linked by relationships themselves determined using sensors. However, such model doesn't allow to manage uncertainty. In order to take into account an uncertainty related to the identification of some entities, we propose to model the set of possible eligible entities, called the universe of discourse, by an anonymous instance in the ontology. This anonymous instance is linked with a “same as” relationships with all possible eligible entities. In addition, we propose to complete this model by the association of a mass with each “same as” relationship. This paper presents a probabilistic semantic to these masses. A simple didactic example on a housing use situations measurement illustrates the presented approach.
{"title":"Uncertainty management of situations in a housing use context","authors":"Cedric Deffo Sikounmo, S. Perrin, E. Benoit","doi":"10.1109/CIVEMSA.2017.7995314","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2017.7995314","url":null,"abstract":"This paper proposes a new contribution to manage uncertainty in the context of a situation recognition. It gives an application to the measurement of housing use situations. It extends a previous communication that proposes an ontological based model of situations. In this model, a situation is a set of entities linked by relationships themselves determined using sensors. However, such model doesn't allow to manage uncertainty. In order to take into account an uncertainty related to the identification of some entities, we propose to model the set of possible eligible entities, called the universe of discourse, by an anonymous instance in the ontology. This anonymous instance is linked with a “same as” relationships with all possible eligible entities. In addition, we propose to complete this model by the association of a mass with each “same as” relationship. This paper presents a probabilistic semantic to these masses. A simple didactic example on a housing use situations measurement illustrates the presented approach.","PeriodicalId":123360,"journal":{"name":"2017 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133635211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.1109/CIVEMSA.2017.7995329
Othmane El Badlaoui, A. Hammouch
In this work, a simple method for separation between normal and abnormal heart sounds (Phonocardiogram) is presented. Mel-Frequency Cepstral Coefficients (MFCC) are extracted from two different datasets of heartbeats. Several Classifiers, such as, Support Vectors Machine (SVM), K-Nearest Neighbors (KNN), Naïve Bayes (NB), Classification Tree (CT) and discriminative analysis (DA), are used. Simulation results obtained from yielding methods are compared and discussed. The developed method (scheme) return good results from deferent dataset. Results obtained by using different classification methods versus two dataset are, significantly, accurate compared to the existing methods.
{"title":"Phonocardiogram classification based on MFCC extraction","authors":"Othmane El Badlaoui, A. Hammouch","doi":"10.1109/CIVEMSA.2017.7995329","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2017.7995329","url":null,"abstract":"In this work, a simple method for separation between normal and abnormal heart sounds (Phonocardiogram) is presented. Mel-Frequency Cepstral Coefficients (MFCC) are extracted from two different datasets of heartbeats. Several Classifiers, such as, Support Vectors Machine (SVM), K-Nearest Neighbors (KNN), Naïve Bayes (NB), Classification Tree (CT) and discriminative analysis (DA), are used. Simulation results obtained from yielding methods are compared and discussed. The developed method (scheme) return good results from deferent dataset. Results obtained by using different classification methods versus two dataset are, significantly, accurate compared to the existing methods.","PeriodicalId":123360,"journal":{"name":"2017 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132766785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.1109/CIVEMSA.2017.7995317
Liviu-Cristian Duţu, J. Tissot, Stéphanie Dabic, G. Mauris, P. Bolon
Driven by the growing complexity of real-world systems, current trends in fuzzy system modeling employ ways to automatically learn the system rule-base from numerical data. While these approaches greatly improve model accuracy, the resulting rule-base is generally less interpretable than expert-driven rule-bases. We provide qualitative justification for this behavior and show that automatic rule-base generation leads to the occurrence of redundant rules, i.e. rules encoding approximately the same knowledge. In order to improve interpretability, redundant rules must be properly detected and removed. Therefore, this paper introduces a novel measure to estimate the redundancy of fuzzy rules based on the common influence exerted by a pair of rules over the data, and weighted by some distance measure between rules. The concept of common influence, defined therein, indicates how two rules are linked by the data distribution. Our approach is validated on some analytical function modeling task and then tested on a real-world problem dealing with vibrotactile stimuli characterization. Both experiments showed that removing the most redundant rules, according to the proposed redundancy measure, yields smaller rule-bases of up to 25%, with only negligible drops in accuracy.
{"title":"A redundancy measure for efficient fuzzy rule-base reduction","authors":"Liviu-Cristian Duţu, J. Tissot, Stéphanie Dabic, G. Mauris, P. Bolon","doi":"10.1109/CIVEMSA.2017.7995317","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2017.7995317","url":null,"abstract":"Driven by the growing complexity of real-world systems, current trends in fuzzy system modeling employ ways to automatically learn the system rule-base from numerical data. While these approaches greatly improve model accuracy, the resulting rule-base is generally less interpretable than expert-driven rule-bases. We provide qualitative justification for this behavior and show that automatic rule-base generation leads to the occurrence of redundant rules, i.e. rules encoding approximately the same knowledge. In order to improve interpretability, redundant rules must be properly detected and removed. Therefore, this paper introduces a novel measure to estimate the redundancy of fuzzy rules based on the common influence exerted by a pair of rules over the data, and weighted by some distance measure between rules. The concept of common influence, defined therein, indicates how two rules are linked by the data distribution. Our approach is validated on some analytical function modeling task and then tested on a real-world problem dealing with vibrotactile stimuli characterization. Both experiments showed that removing the most redundant rules, according to the proposed redundancy measure, yields smaller rule-bases of up to 25%, with only negligible drops in accuracy.","PeriodicalId":123360,"journal":{"name":"2017 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124574888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.1109/CIVEMSA.2017.7995301
Diadié Sow, A. Imoussaten, P. Couturier, J. Montmain
In a highly competitive and unstable environment, manufacturers must constantly improve their products to remain competitive and satisfy their customers while minimizing incurred costs and risk taking. At the early stages of (re-) engineering, performances forecasting of new product is complicated. Indeed, the impacts of any characteristic change on the product performance are not precisely known. Decision-makers must thus identify the performances to be improved while limiting the engineering efforts spent on innovative upgrades. Although some theoretical worth indexes have been proposed in the multiple criteria literature to estimate the expectable gains when improving changes are planned, they generally rely on non-realistic assumptions on the achievability of the expected improvements. Based on multi-criteria decision analysis techniques and uncertainty theory, this paper proposes an extension of the worth index concept when the likelihood of the expected improvements is not precisely known as it is the case at the preliminary stages of design activities.
{"title":"A possibilistic framework for identifying the performance to be improved in the imprecise context of preliminary design stage","authors":"Diadié Sow, A. Imoussaten, P. Couturier, J. Montmain","doi":"10.1109/CIVEMSA.2017.7995301","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2017.7995301","url":null,"abstract":"In a highly competitive and unstable environment, manufacturers must constantly improve their products to remain competitive and satisfy their customers while minimizing incurred costs and risk taking. At the early stages of (re-) engineering, performances forecasting of new product is complicated. Indeed, the impacts of any characteristic change on the product performance are not precisely known. Decision-makers must thus identify the performances to be improved while limiting the engineering efforts spent on innovative upgrades. Although some theoretical worth indexes have been proposed in the multiple criteria literature to estimate the expectable gains when improving changes are planned, they generally rely on non-realistic assumptions on the achievability of the expected improvements. Based on multi-criteria decision analysis techniques and uncertainty theory, this paper proposes an extension of the worth index concept when the likelihood of the expected improvements is not precisely known as it is the case at the preliminary stages of design activities.","PeriodicalId":123360,"journal":{"name":"2017 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123079132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.1109/CIVEMSA.2017.7995330
R. Romdhane, Youness Lami, D. Genon-Catalot, N. Fourty, A. Lagrèze, D. Jongmans, L. Baillet
Landslides, of slip/cast type, dynamics are mainly characterised by a sudden solid to fluid transition during heavy rain events. This feature makes them rather difficult to predict and therefore remains a major threat to nearby populated valleys. Our multidisciplinary partnership between laboratories (ISTerre: earth science and LCIS: embedded electronics, telecommunication) aims at developing a new predictive tool in order to analyse field movements using sensors. The plan is to instrument unstable slopes with a sensors network, characterised by its low consumption and cost, in order to achieve continuous monitoring of the overall shape deformation. Other monitoring techniques can be used for this particular phenomenon (photogrammetry, LIDAR …), but some significant imperfections and flaws lay within their usage. This paper presents the methods used to enable geolocation using our wireless sensors network based on LoRa (Long Range) radio transmission technology.
{"title":"Wireless sensors network for landslides prevention","authors":"R. Romdhane, Youness Lami, D. Genon-Catalot, N. Fourty, A. Lagrèze, D. Jongmans, L. Baillet","doi":"10.1109/CIVEMSA.2017.7995330","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2017.7995330","url":null,"abstract":"Landslides, of slip/cast type, dynamics are mainly characterised by a sudden solid to fluid transition during heavy rain events. This feature makes them rather difficult to predict and therefore remains a major threat to nearby populated valleys. Our multidisciplinary partnership between laboratories (ISTerre: earth science and LCIS: embedded electronics, telecommunication) aims at developing a new predictive tool in order to analyse field movements using sensors. The plan is to instrument unstable slopes with a sensors network, characterised by its low consumption and cost, in order to achieve continuous monitoring of the overall shape deformation. Other monitoring techniques can be used for this particular phenomenon (photogrammetry, LIDAR …), but some significant imperfections and flaws lay within their usage. This paper presents the methods used to enable geolocation using our wireless sensors network based on LoRa (Long Range) radio transmission technology.","PeriodicalId":123360,"journal":{"name":"2017 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115682990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.1109/CIVEMSA.2017.7995318
A. Trad, D. Kalpić
The authors based their Research and Development Project (RDP) on a mixed research method that is mainly based on intelligent neural networks and action research reasoning approach; where both methods are very similar and resemble to the human brain structure and its way of functioning. The applied research method is founded on a real life case for detecting and processing heuristic algorithms for business transformation patterns using a high level neural network implementation environment. The proposed RDP offers a set of solutions in the form of technical and managerial recommendations, to be used by company's business analysts and engineers to implement intelligent solutions for services-based Business Transformation Projects (BTP). Action Research (AR) is applied mainly in education research that corresponds to the Architecture Transformation Projects (ATP) or BTP's capability to achieve business intelligence objectives, because it inspects and learns from configurable intelligent micro artefacts that are found in the proposed neural networks concept that can be applied to BTPs' implementation phase [4]. The RDP is not influenced by any specific business domain and is considered to be generic and holistic; where a brain-like neural networks business infrastructure is based on: 1) Neural Networks and Enterprise Architecture's (NNEA); and 2) Agnostic Implementation Environment (AIE). This NNEA is based on a reasoning concept that is basically a qualitative research method that manages and qualifies Critical Success Factors (CSF) sets, actions and final solutions for the BTPs support [5]. The RDP's underlined system supports the BTPs in integrating micro artefact scenarios that are in fact a set of interactive atomic service actions. AIE manages atomic services that makes them more advanced and more flexible than the rigid and monolithic micro services proposal.
{"title":"A Neural Networks portable and Agnostic Implementation Environment for Business Transformation Projects the basic structure","authors":"A. Trad, D. Kalpić","doi":"10.1109/CIVEMSA.2017.7995318","DOIUrl":"https://doi.org/10.1109/CIVEMSA.2017.7995318","url":null,"abstract":"The authors based their Research and Development Project (RDP) on a mixed research method that is mainly based on intelligent neural networks and action research reasoning approach; where both methods are very similar and resemble to the human brain structure and its way of functioning. The applied research method is founded on a real life case for detecting and processing heuristic algorithms for business transformation patterns using a high level neural network implementation environment. The proposed RDP offers a set of solutions in the form of technical and managerial recommendations, to be used by company's business analysts and engineers to implement intelligent solutions for services-based Business Transformation Projects (BTP). Action Research (AR) is applied mainly in education research that corresponds to the Architecture Transformation Projects (ATP) or BTP's capability to achieve business intelligence objectives, because it inspects and learns from configurable intelligent micro artefacts that are found in the proposed neural networks concept that can be applied to BTPs' implementation phase [4]. The RDP is not influenced by any specific business domain and is considered to be generic and holistic; where a brain-like neural networks business infrastructure is based on: 1) Neural Networks and Enterprise Architecture's (NNEA); and 2) Agnostic Implementation Environment (AIE). This NNEA is based on a reasoning concept that is basically a qualitative research method that manages and qualifies Critical Success Factors (CSF) sets, actions and final solutions for the BTPs support [5]. The RDP's underlined system supports the BTPs in integrating micro artefact scenarios that are in fact a set of interactive atomic service actions. AIE manages atomic services that makes them more advanced and more flexible than the rigid and monolithic micro services proposal.","PeriodicalId":123360,"journal":{"name":"2017 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131190315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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