The use of Fog computing for real-time Big data monitoring of power consumption is gaining popularity. In traditional systems, Cloud servers receive sensor Big data, perform predictions and detect anomalies or any thr...
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ISBN:
(纸本)9781728170220
The use of Fog computing for real-time Big data monitoring of power consumption is gaining popularity. In traditional systems, Cloud servers receive sensor Big data, perform predictions and detect anomalies or any threat patterns and then raise the alarms. With exponentially increasing sensor data, Cloud servers are becoming impractical to process this data because of the issues of volume, velocity, variety, network bandwidth, real-time support and security issues. Fog computing is introduced as a Distributed computing paradigm that uses intermediate computing infrastructure for processing to overcome the limitations of Cloud computing. In this paper, we propose a hierarchically Distributed Fog computing architecture to deploy machine learning based anomaly detection models for generating insights from the collected smart meter sensor data from the household. The anomaly detection is divided into two steps: model training and anomaly detection. We perform detailed analysis and evaluation of the models using standard open datasets obtained from UCI machine learning repository. The results confirm the efficacy of our proposed architecture. We used open source framework and software for our experiments.
Mobile edge computing (MEC) has been considered as a promising technique to support computation-intensive and latency-sensitive multimedia applications (e.g., video analytics and real-time target tracking) in future 5...
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Agriculture is the main supporting sector of Indian economy and most of the rural population's livelihood depends on it. Crop yielding has been decreasing day by day because it's growth mainly depends on monso...
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ISBN:
(数字)9783030372187
ISBN:
(纸本)9783030372187;9783030372170
Agriculture is the main supporting sector of Indian economy and most of the rural population's livelihood depends on it. Crop yielding has been decreasing day by day because it's growth mainly depends on monsoon which is highly unpredictable in India. Further, the crop growth also depends on soil parameters, which varies due to ground contamination. For increasing the crop productivity, there is a need to incorporate newtechnologies in the field of agriculture. By utilizing new technologies like Machine Learning and Internet of Things applications in the field of agriculture will be enhance the financial growth of the country. Here, we have presented a framework which mainly focuses on agriculture in Tumakuru district of Karnataka that uses Naive Bayes classification method to suggest the farmers with the best suitable crop for sowing in that particular environmental condition.
The proceedings contain 50 papers. The special focus in this conference is on Computational Methods and data Engineering. The topics include: On roman domination of graphs using a genetic algorithm;general variable ne...
ISBN:
(纸本)9789811568756
The proceedings contain 50 papers. The special focus in this conference is on Computational Methods and data Engineering. The topics include: On roman domination of graphs using a genetic algorithm;general variable neighborhood search for the minimum stretch spanning tree problem;tabu-embedded simulated annealing algorithm for profile minimization problem;deep learning-based asset prognostics;evaluation of two feature extraction techniques for age-invariant face recognition;XGBoost: 2D-object recognition using shape descriptors and extreme gradient boosting classifier;Comparison of principle component analysis and stacked autoencoder on NSL-KDD dataset;maintainability configuration for component-based systems using fuzzy approach;development of petri net-based design model for energy efficiency in wireless sensor networks;Hybrid ANFIS-GA and ANFIS-PSO based models for prediction of type 2 diabetes mellitus;lifting wavelet and discrete cosine transform-based super-resolution for satellite image fusion;biologically inspired intelligent machine and its correlation to free will;weather status prediction of Dhaka City using machine learning;image processing: What, how and future;a study of efficient methods for selecting quasi-identifier for privacy-preserving data mining;day-ahead wind power forecasting using machine learning algorithms;query relational databases in Punjabi language;machine learning algorithms for big dataanalytics;fault classification using support vectors for unmanned helicopters;EEG signal analysis and emotion classification using bispectrum;social network analysis of youtube: A case study on content diversity and genre recommendation;Slack feedback analyzer (SFbA);a review of tools and techniques for preprocessing of textual data;A U-shaped printed UWB antenna with three band rejection;model for predicting academic performance through artificial intelligence.
intelligent Transportation System (ITS) is positioned at the confluence of the two most powerful currents of our time, information technology empowered by artificial intelligence and the ever-improving transportation ...
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Classification is a supervised learning process that is used to predict target class for an input variable. In an imbalanced dataset, the total count of examples of minority class is comparatively less than the total ...
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data mining is an important subfield of data Science and is also called knowledge discovery within a database. In this paper, we actually use data mining visualization techniques to analyze the huge database of Distri...
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ISBN:
(纸本)9789811510847;9789811510830
data mining is an important subfield of data Science and is also called knowledge discovery within a database. In this paper, we actually use data mining visualization techniques to analyze the huge database of District Shopian and assume prevalence rate of HCV in Specific Area (Vehil) of District Shopian (J&K). Health Department of District Shopian uses different types of registers to maintain the data of patients. During survey, we go through the registers to collect data of symptomatic HCV patients analyze it by maintaining the disease trends. data mining analytical tools were being used to detect prevalence of HCV infection distribution and also identify the reasons that contributed to such widespread of HCV in the area of Vehil
data transmission and real-time processing of Internet of Things (IoT) devices in remote unmanned area are becoming a challenging issue. In this paper, an Unmanned Aerial Vehicle (UAV) enabled computing system is inve...
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ISBN:
(纸本)9781728173276
data transmission and real-time processing of Internet of Things (IoT) devices in remote unmanned area are becoming a challenging issue. In this paper, an Unmanned Aerial Vehicle (UAV) enabled computing system is investigated in a smart farm, where multiple UAVs are deployed to make intelligent decisions based on data collected by sensors. First, considering the delay constraint of data processing, the concept of effective data is introduced. Next, the effective data of farm monitoring devices (FMDs) is maximized by jointly optimizing computing and communication resources allocation and the deployment of UAVs. The formulated problem is a combinatorial optimization problem that is hard to tackle. Furthermore, this problem is transformed into two sub-problems and a two-layer iterative optimization algorithm is proposed to get an approximate optimal solution. Finally, simulation results demonstrate that the proposed algorithm has a significant increase in terms of effective data.
The frequency response method is one of the most commonly used methods for determining the winding deformation of a power transformer. However, in the actual measurement, the frequency response curve of the test resul...
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The delivery of computing services including storage, databases, networking, software, analytics, intelligence and more is moving from the cloud towards the edge;among all technical requirements, the edge needs to be ...
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ISBN:
(纸本)9781728184234
The delivery of computing services including storage, databases, networking, software, analytics, intelligence and more is moving from the cloud towards the edge;among all technical requirements, the edge needs to be able to natively support artificial intelligence processes to enable new technological paradigms, such as smart Factory 4.0, healthcare assisted living, smart cities and advanced robotics, for example In this paper, we will present the enabling technologies to will be developed within the "Big data processing and artificial intelligence at the network edge" (BRAINE) project, one of the largest joint activities in Europe in the area of edge computing enabling artificial intelligence. BRAINE covers the full stack of a system solution, from subsystem integration up to artificial intelligence service provisioning, and includes four use cases of direct impact in the European ecosystem.
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