AMI smart meters are the advanced meters capable of measuring customer energy consumption at a fine-grained time interval, e.g., every 5 minutes, 15 minutes etc. The data are very sizable, and might be from different ...
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ISBN:
(纸本)9781538643877
AMI smart meters are the advanced meters capable of measuring customer energy consumption at a fine-grained time interval, e.g., every 5 minutes, 15 minutes etc. The data are very sizable, and might be from different sources, along with the other social-economic metrics, which make the data management very complex. A smart grid is an intelligent electricity grid that optimizes the generation, distribution and consumption of electricity through the introduction of Information and Communication Technologies on the electricity grid. Deployment of smart grids gives space to an occurrence of new methods of machine learning and data analysis. smart grids can contain a millions of smart meters, which produce a large amount of data of electricity consumption (long time series). Big data technologies offers suitable solutions for utilities. This paper presents a thorough analysis of 5-minutes 100 anonymized commercial buildings meter data sets to explore time series of electricity consumption and on the creation of a simple forecast model, which uses similar day approach. Our big dataanalytics can help energy companies to improve the management of energy and services, support intelligent grid control, make an accurate forecast or to detect anomalies.
Road accidents are becoming very common in the country. The impact of road accidents can lead to the loss of many lives and can also damage many body parts. This situation becomes more serious if the riders won't ...
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ISBN:
(数字)9781728198859
ISBN:
(纸本)9781728198866
Road accidents are becoming very common in the country. The impact of road accidents can lead to the loss of many lives and can also damage many body parts. This situation becomes more serious if the riders won't wear the helmet which can be prevented by wearing the helmet and can reduce these impacts. While riding the bike, the government made it a mandatory rule to wear the helmet. Using this rule as a base, a smart helmet system is proposed which helps in providing safety to the riders and prevents accidents. The system mainly consists of Arduino Uno as a processor for processing the data, GSM & GPS modules for tracking the location and sending a message to authorized numbers, a wiper for wiping the raindrops on the helmet screen, a vibration sensor for alerting, in case the rider meets an accident and alcohol sensors as breath analyzer for the rider. The system will ensure a safe journey for riders and gives a helping hand in case of emergency. The cost of installing the whole system onto the helmet is affordable.
Due to the rapid change in technologies, new data forms exist which lead to a huge data size on the internet. As a result, some learning platforms such as e-learning systems must change their methodologies for data pr...
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ISBN:
(纸本)9783319746906;9783319746890
Due to the rapid change in technologies, new data forms exist which lead to a huge data size on the internet. As a result, some learning platforms such as e-learning systems must change their methodologies for data processing to be smarter. This paper proposes a framework for smoothly adapt the traditional e-learning systems to be suitable for smart cities applications. Learning analytics (LA) has turned into a noticeable worldview with regards to instruction of late which embraces the current progressions of innovation, for example, cloud computing, big data processing, and Internet of Things. LA additionally requires a concentrated measure of preparing assets to create applicable investigative outcomes. Be that as it may, the customary methodologies have been wasteful at handling LA difficulties.
The confluence of technological and societal advances, and more specifically, engagement with Web, social media, and smart devices has the potential to affect the mental behavior of the individuals. Examples include e...
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ISBN:
(纸本)9781450371780
The confluence of technological and societal advances, and more specifically, engagement with Web, social media, and smart devices has the potential to affect the mental behavior of the individuals. Examples include extremist and criminal behaviors such as radicalization and cyber-bullying, which are causing serious issues for humanity. Major barriers to the effective understanding of behavioral disorders on social networks includes the ability to understand the content and context of social documents, as well as the activity of social users. Understanding the patterns of behavioral disorders (e.g., criminal and extremist activities) on social networks, is challenging and requires techniques to contextualize the content of social documents based on the time-aware analysis of personality, behaviour and past activities of social users. In this context, semantic information extraction and enrichment from social documents has the potential to become a vital asset to explore the sign of behavioral disorders and prevent serious issues such as cyber-bullying, suicidal related behavior and radicalization. To address this challenge, in this paper, we present a novel social document analysis pipeline to enable analysts engage with social documents (e.g., a Tweet in Twitter or a post on Facebook) to explore cognitive aspects of behavioral disorders. We implement the pipeline as an extensible and scalable architecture and present the evaluation results.
Digital transformation of a railway system based on big data technologies relies on integrating large volumes of streaming data into digitally enabled enterprise systems to form a comprehensive and efficient intellige...
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ISBN:
(数字)9781728162515
ISBN:
(纸本)9781728162522
Digital transformation of a railway system based on big data technologies relies on integrating large volumes of streaming data into digitally enabled enterprise systems to form a comprehensive and efficient intelligent transportation system. data requirements of the smart railway transportation involve a large number of unstructured data and semi-structured data including railway KPI data. Traditional ETL technology cannot cope with fast growing demands of processing large volumes of real-time data collected from heterogeneous sources both inside the system and in the environment. According to the characteristics of the railway KPI data, this paper proposes the designs of an automated ETL system with higher versatility and efficiency of data processing. To reach the goals, we optimize the workflow of the ETL using a proprietary designed metadata management framework. Making ETL suitable for big data-driven railway transportation environment, requires redesigning the ETL processing rules by using metadata model and then optimizing the extracting, transforming and loading processes of the ETL system. Our experimental results with actual railway KPI data show that the proposed metadata supported automated ETL system can effectively serve the railway KPI data processing using open source distributed big data technologies. The proposed metadata framework proved to be efficient in processing complex data structures and large data capacity of big data.
With the rapid growth of the population, the resulting amount of pedestrian traffic puts greater pressure on the traffic management and travel services of cities. The original-destination analysis of residents' tr...
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ISBN:
(数字)9781728131290
ISBN:
(纸本)9781728131306
With the rapid growth of the population, the resulting amount of pedestrian traffic puts greater pressure on the traffic management and travel services of cities. The original-destination analysis of residents' travel can effectively promote the optimization of urban regional traffic planning and the release of accurate traffic information. The rapid construction of the cellular network and the expansion of the personal smart phone, with which the user terminal interacts with the cellular network, generate a large amount of communication data, including additional time for the intelligent terminal to transmit the carrier base station. This paper proposes a mobile phone signaling-based user travel feature recognition and road network traffic monitoring system. This solution uses mobile phones as a probe to collect vehicle signaling data along the road to evaluate vehicle distribution and road traffic flow. It reflects the congestion status of the road, simultaneously analyzes the user's travel characteristics and regional distribution in the area through user trajectory, and dynamically evaluates the running status of urban road traffic.
Blockchain is developing rapidly in various domains for its security. Nowadays, one of the most crucial fundamental concerns is internet security. Blockchain is a novel solution to enhance the security of network appl...
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ISBN:
(数字)9781728189987
ISBN:
(纸本)9781728189994
Blockchain is developing rapidly in various domains for its security. Nowadays, one of the most crucial fundamental concerns is internet security. Blockchain is a novel solution to enhance the security of network applications. However, there are no precise frameworks to secure the Internet of Vehicle (IoV) using Blockchain technology. In this paper, a blockchain-based smart internet of vehicle (BSIoV) framework has been proposed due to the cooperative, collaborative, transparent, and secure characteristics of Blockchain. The main contribution of the proposed work is to connect vehicle-related authorities together to fix a secure and transparent vehicle-to-everything (V2X) communication through the peer-to-peer network connection and provide secure services to the intelligent transport systems. A key management strategy has been included to identify a vehicle in this proposed system. The proposed framework can also provide a significant solution for the data security and safety of the connected vehicles in blockchain network.
The trend of IoT is increasing day by day, making each and everything related to daily life a smart thing. Making things smart also reduces the need for manpower;in addition, the work is done appropriately as it decre...
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Many cities around the world implement the intelligent Transportation Systems (ITS) concept to reduce road traffic congestion. This concept implies the usage of Internet of Things (IoT) technologies to ensure a better...
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ISBN:
(数字)9781728170169
ISBN:
(纸本)9781728170176
Many cities around the world implement the intelligent Transportation Systems (ITS) concept to reduce road traffic congestion. This concept implies the usage of Internet of Things (IoT) technologies to ensure a better traffic flow, especially in crowded urban areas. Sensors networks became part of road infrastructure and have as main responsibilities to collect real-time traffic data and to send them to Traffic Management Centres (TMCs) which control further the traffic lights timings. Today's technologies meet some limitations in terms of efficiency. This paper starts with an overview of these limitations to create a path for discussing the challenges that the development of ITS will meet in the context of Future Networks (FN) 2030 concept. Based on this development path, the identification of current limitations and possible future challenges consists of an important step of this research. Further, the main contribution in this research is to show how the ITS shall adapt to meet the requirements of FN 2030 by providing an architecture for Future ITS 2030 that meets the general ITS needs.
Wrist-worn smart devices are providing increased insights into human health, behaviour and performance through sophisticated analytics. However, battery life, device cost and sensor performance in the face of movement...
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ISBN:
(数字)9781728147161
ISBN:
(纸本)9781728147178
Wrist-worn smart devices are providing increased insights into human health, behaviour and performance through sophisticated analytics. However, battery life, device cost and sensor performance in the face of movement-related artefact present challenges which must be further addressed to see effective applications and wider adoption through commoditisation of the technology. We address these challenges by demonstrating, through using a simple optical measurement, photoplethysmography (PPG) used conventionally for heart rate detection in wrist-worn sensors, that we can provide improved heart rate and human activity recognition (HAR) simultaneously at low sample rates, without an inertial measurement unit. This simplifies hardware design and reduces costs and power budgets. We apply two deep learning pipelines, one for human activity recognition and one for heart rate estimation. HAR is achieved through the application of a visual classification approach, capable of robust performance at low sample rates. Here, transfer learning is leveraged to retrain a convolutional neural network (CNN) to distinguish characteristics of the PPG during different human activities. For heart rate estimation we use a CNN adopted for regression which maps noisy optical signals to heart rate estimates. In both cases, comparisons are made with leading conventional approaches. Our results demonstrate a low sampling frequency can achieve good performance without significant degradation of accuracy. 5 Hz and 10 Hz were shown to have 80.2% and 83.0% classification accuracy for HAR respectively. These same sampling frequencies also yielded a robust heart rate estimation which was comparative with that achieved at the more energy-intensive rate of 256 Hz.
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