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Sensors data collection architecture in the Internet of Mobile Things as a service (IoMTaaS) platform

Sensors data collection architecture in the Internet of Mobi...

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international conference on I-SMAC (IoT in Social, Mobile, analytics and Cloud) (I-SMAC)

作者： Maiti, Prasenjit Sahoo, Bibhudatta Turuk, Ashok Kumar Satpathy, Suchismita Natl Inst Technol Dept Comp Sci & Engn Rourkela Odisha India

ISBN: (纸本)9781509032433

smart object interconnected between each other and producing a large volume of information in Internet of Mobile Things (IoMT) is a huge challenge. The things that we expect to connect to the Internet will consist of sensors, actuators with information processing and communication capabilities that will make themselves intelligent. Sensors are collecting continuously environmental data (e.g. body area network, smart city, cars, smartphones, etc.). We used Arduino, XBee, Raspberry Pi 3 and open source software for framework design. This architecture process real-time data and maximize the delivery of raw data to the cloud for post processing. It also ensure efficient eventdriven data collection given the buffer space and communication bandwidth limitations of each sensor. An intelligent IoMT gateway and middleware used to support different message format of sensor data and efficient decision-making system. We also propose an Android data collection system where data collectors are smartphones. This paper defines a data collection architecture supporting the physical dimension of sensors to the storage of data in a cloud-based service. This class of architecture must tackle several challenges, e.g., buffer management, sensor message ordering, data alignment for multiple temporal data streams, data storage, sensor heterogeneity, high throughput and avoiding processing bottlenecks. For the issues of an extended advancement cycle, poor transportability and high-chance in the improvement procedure of ZigBee remote system, presents the Unified Modeling Language (UML) to institutionalize the advancement procedure, enhancing improvement productivity and guaranteeing item quality.

关键词： Architecture Cloud data collection Distributed computing Sensors UML

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data Model Logger - data Discovery for Extract-Transform-Load 19

Data Model Logger - Data Discovery for Extract-Transform-Loa...

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19th IEEE international conference on High Performance computing and Communications (HPCC) / 15th IEEE international conference on smart City (smartCity) / 3rd IEEE international conference on data Science and Systems (DSS)

作者： Madhikermi, Manik Buda, Andrea Dave, Bhargav Framling, Kary Aalto Univ Sch Sci POB 15400 FI-00076 Espoo Finland

ISBN: (纸本)9781538625880

Information Systems (ISs) are fundamental to streamline operations and support processes of any modern enterprise. Being able to perform analytics over the data managed in various enterprise ISs is becoming increasingly important for organisational growth. Extract, Transform, and Load (ETL) are the necessary pre-processing steps of any data mining activity. Due to the complexity of modern IS, extracting data is becoming increasingly complicated and time-consuming. In order to ease the process, this paper proposes a methodology and the results of a pilot implementation, that aims to simplify data extraction process by leveraging the end-users' knowledge and understanding of the specific IS.

关键词： ETL database Trigger Reverse Engineering data Warehouse Information System Information Retrieval Process Mapping data Discovery

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Impact of NOx emissions on climate and monitoring using smart sensor technology

Impact of NOx emissions on climate and monitoring using smar...

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2017 international conference on Energy, Communication, data analytics and Soft computing, ICECDS 2017

作者： Sujatha, K. Ponmagal, R.S. Nallamilli, P.G. Bhavani Kalpalatha, T. EEE/CSE Dept. Center for Electronics Automation and Industrial Research Dr. MGR Educational and Research Institute Maduravoyal Chennai-95 India EEE Dept. Center for Electronics Automation and Industrial Research Dr. MGR Educational and Research Institute Maduravoyal Chennai-95 India ECE Dept. SKR Engineering College Nazrathpeth Chennai India

ISBN: (纸本)9781538618868

Human resource is of great assert, as it is the gift of nature. Exploitation of human resources should strictly be monitored on health aspects. The power generation sectors in view to increase the combustion quality for enhancing the power production contribute to green house gases which is a threat to human health. The prime aspiration is in detection, recognition and understanding of combustion conditions in power plants ensuring low Nitrogen Oxide (NOx) emissions for protecting the human health from hazardous gases. The colour information from the furnace flame images is the foundation for this scheme. The process of estimating the NOx emissions using a feed forward controller is implemented using Back propagation Algorithm (BPA) and Ant Colony Optimization (ACO). The challenge lies in identification of the 10 attributes used for training the ANN so as to estimate the NOx emissions. The estimation by ANN is termed as intelligent sensors embedded in the computing system to monitor using (IoT). This method proves to be indispensable because this IoT based online monitoring has reduced the percentage of emissions by 19% thereby increasing the combustion quality which has profound effect on human health. © 2017 IEEE.

关键词： Internet of things

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An Edge Based smart Parking Solution Using Camera Networks and Deep Learning

An Edge Based Smart Parking Solution Using Camera Networks a...

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IEEE international conference on Cognitive computing (ICCC)

作者： Harshitha Bura Nathan Lin Naveen Kumar Sangram Malekar Sushma Nagaraj Kaikai Liu Computer Engineering Department San José State University (SJSU) San José CA USA

The smart parking industry continues to evolve as an increasing number of cities struggle with traffic congestion and inadequate parking availability. For urban dwellers, few things are more irritating than anxiously searching for a parking space. Research results show that as much as 30% of traffic is caused by drivers driving around looking for parking spaces in congested city areas. There has been considerable activity among researchers to develop smart technologies that can help drivers find a parking spot with greater ease, not only reducing traffic congestion but also the subsequent air pollution. Many existing solutions deploy sensors in every parking spot to address the automatic parking spot detection problems. However, the device and deployment costs are very high, especially for some large and old parking structures. A wide variety of other technological innovations are beginning to enable more adaptable systems-including license plate number detection, smart parking meter, and vision-based parking spot detection. In this paper, we propose to design a more adaptable and affordable smart parking system via distributed cameras, edge computing, data analytics, and advanced deep learning algorithms. Specifically, we deploy cameras with zoom-lens and motorized head to capture license plate numbers by tracking the vehicles when they enter or leave the parking lot; cameras with wide angle fish-eye lens will monitor the large parking lot via our custom designed deep neural network. We further optimize the algorithm and enable the real-time deep learning inference in an edge device. Through the intelligent algorithm, we can significantly reduce the cost of existing systems, while achieving a more adaptable solution. For example, our system can automatically detect when a car enters the parking space, the location of the parking spot, and precisely charge the parking fee and associate this with the license plate number.

关键词： Cameras Licenses Sensors Laser radar Automobiles Feature extraction databases

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A Generic stack frame work for Internet Of Things

A Generic stack frame work for Internet Of Things

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international conference on Communication, computing and Internet of Things (IC3IoT)

作者： Rakesh Kumar Ambhati Chaudhari Y Shashikant Valluri Sarimela Department of Electrical Engineering UEM Kolkata Department of Electronics and Communication Engineering IEM Kolkata School of Electric al and Electronic Engineering University of Manchester Manchester UK

ISBN: (纸本)9781538624609;9781538624593

Internet of things (IOT) does affect every aspect of human life severely, as it is envisioned to bridge physical world and virtual world. Automation and convenience are vital value addition to human life, by IOT phenomena. The growth of IoT technologies is primarily contributed by four factors. 1) Declining cost of sensors, 2) Increasing broadband penetration, 3) Cheap data storage and 4) Advanced software analytics, that can transform raw sensor data into vital knowledge. smart Home personal area networks(PANs), Industrial grids, Health care body area networks(BANs) and even Military vehicular networks will benefit from IOT concepts. However all the above mentioned areas have different IOT stack requirements. As different IOT networks do encounter issues like spectrum crunch, increased interference, Green energy, heterogeneity and coverage issues at varying degree of intensity. In this paper a broad classification of IOT networks is illustrated, form their stack requirements perspective. This paper also covers emerging Industry standardization efforts, to develop frameworks, API and platforms to realize IOT vision.

关键词： Internet of Things intelligent sensors Wireless sensor networks Monitoring Protocols Software

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Distributed Sensor data computing in smart City Applications 18

Distributed Sensor Data Computing in Smart City Applications

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18th IEEE international Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM)

作者： Wang, Wei De, Suparna Zhou, Yuchao Huang, Xin Moessner, Klaus Xian Jiaotong Liverpool Univ Dept Comp Sci & Software Engn Suzhou Peoples R China Univ Surrey Elect & Elect Engn Dept Inst Commun Syst Guildford Surrey England

ISBN: (纸本)9781538627235

With technologies developed in the Internet of Things, embedded devices can be built into every fabric of urban environments and connected to each other;and data continuously produced by these devices can be processed, integrated at different levels, and made available in standard formats through open services. The data, obviously f a form of "big data", is now seen as the most valuable asset in developing intelligent applications. As the sizes of the IoT data continue to grow, it becomes inefficient to transfer all the raw data to a centralised, cloud-based data centre and to perform efficient analytics even with the state-of-the-art big data processing technologies. To address the problem, this article demonstrates the idea of "distributed intelligence" for sensor data computing, which disperses intelligent computation to the much smaller while autonomous units, e.g., sensor network gateways, smart phones or edge clouds in order to reduce data sizes and to provide high quality data for data centres. As these autonomous units are usually in close proximity to data consumers, they also provide potential for reduced latency and improved quality of services. We present our research on designing methods and apparatus for distributed computing on sensor data, e.g., acquisition, discovery, and estimation, and provide a case study on urban air pollution monitoring and visualisation.

关键词： Internet of Things Distributed Intelligence Sensor data Sensor Services smart city

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A Science Cloud for smart Cities Research

A Science Cloud for Smart Cities Research

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7th international conference on Future Buildings and Districts - Energy Efficiency from Nano to Urban Scale (CISBAT)

作者： Heller, A. Liu, X. Gianniou, P. Tech Univ Denmark Dept Civil Engn Brovej 1 DK-2800 Lyngby Denmark Tech Univ Denmark Dept Engn Management Prod Storvet DK-2800 Lyngby Denmark

ISBN: (纸本)9781510848498

Cities are densely populated and heavily equipped areas with a high level of service provision. smart cities can use these conditions to achieve the goals of a smart society for their citizens. To facilitate such developments, the necessary IT-infrastructure has to be in place for supporting, amongst many other things, the whole lifecycle of big data management and analytics for research activities. At the Centre for IT-intelligent smart Energy for Cities, we have therefore been developing a flexible infrastructure, based on open sourcetechnologies. This paper presents this solution and its application in a city and building research. (C) 2017 The Authors. Published by Elsevier Ltd.

关键词： Infrastructure for smart cities cloud computing big data research case examples building application

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intelligent stacking system

Intelligent stacking system

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2017 international conference on Energy, Communication, data analytics and Soft computing, ICECDS 2017

作者： Ahmed, Shafeequerrahman S. Annadate, Suresh A. Department of Electronics Engineering Jawaharlal Nehru Engineering College AurangabadMaharashtra India

ISBN: (纸本)9781538618868

Discussed in this paper is the concept of intelligent automation in medium and small-scale industries and that are involved in the manufacturing of small objects such as ball bearing in this case. It is an electromechanical system which includes certain mechanical parts followed by certain electronic assemblies properly interfaced to achieve the required motion in desired direction could be achieved through which the object available at the output could be moved towards the stacking unit. In this work, I tried to introduce a little bit of intelligence for stacking a product available at the output of a manufacturing unit. The electromechanical stacking assembly is microcontroller based unit. Programmable logic controller is a conventional option for manufacturing the stacking unit but microcontroller based system seems to be a better choice to upgrade the system for desired modification in the system for various requirements of the industry. For increasing more control capacity, we can use smart components such as intelligent proximity sensor module. No sooner bearing is available at the output, sensing is immediately initiated by a smart inductive sensor. The output will be processed by microcontroller card which will be driving the assembly in order to stack it properly. This paper is an effort for introduction of smartness in the current system shown. Provision is made to keep track of count of the total number of bearings to be packed and will not only be displayed on a liquid crystal display screen for real time reference but it could be sent as text message to the supervisor and a provision is also be made using a higher level language using hyper terminal of the computer. Now a conceptual modification could be the interfacing of entire semi electromechanical system to an intelligent system. © 2017 IEEE.

关键词： Microcontrollers

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CoTWare: A Cloud of Things Middleware 37

CoTWare: A Cloud of Things Middleware

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37th IEEE international conference on Distributed computing Systems (ICDCS)

作者： Al-Jaroodi, Jameela Mohamed, Nader Jawhar, Imad Mahmoud, Sara Robert Morris Univ Dept Engn Moon PA 15108 USA Middleware Technol Lab Isa Town Bahrain Midcomp Res Ctr Saida Lebanon UAE Univ Coll Informat Technol Al Ain U Arab Emirates

ISBN: (纸本)9781538632932

Applications integrating software with a large number of physical objects and devices in a large-scale Internet of Things (IoT) networks are on the rise. Some examples of these applications are smart grids and water networks and intelligent transportation systems. As they operate in and control a large heterogeneous environment, these applications need real-time controls, powerful and scalable data storage and processing capabilities, and advanced data analytics mechanisms. One of the promising technologies to support such applications is the Cloud of Things (CoT). CoT can provide a platform for linking an IoT with Cloud computing (CC). Another technology that can be utilized for enhancing IoT applications is Fog computing, which extends the traditional Cloud computing paradigm to the edge of the network to enable better support for operating enhanced services closer to the physical environment. However, proper integration and efficient utilization of CoT and Fog computing for large-scale IoT applications is not an easy task This paper proposes a service-oriented middleware, called CoTWare, to facilitate effective integration and utilization of CoT and Fog computing for large-scale IoT applications.

关键词： Cloud of Things Internet of Things Middleware Service Oriented Middleware Fog computing

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Storage Solution of Spatial-Temporal data for Water Monitoring Infrastructures used in smart Cities 21

Storage Solution of Spatial-Temporal Data for Water Monitori...

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21st international conference on Control Systems and Computer Science (CSCS)

作者： Negru, Catalin Pop, Florin Mocanu, Mariana Cristea, Valentin Univ Politehn Bucuresti Comp Sci Dept Bucharest Romania Natl Inst Res & Dev Informat ICI Bucharest Romania

ISBN: (纸本)9781538618394

smart Cities make use of complex utility infrastructure systems such as water distribution. These infrastructures have raised management costs due to improper resource utilization and maintenance or aging infrastructure. New innovative information systems are essential to overcome these issues. Due to the continuous growth of infrastructure systems of smart cities in scope and scale, led to the usage of spatial-temporal networks. The data generated have to be stored in an efficient and scalable way in order to be used by applications such as spatial and temporal analytics or monitoring applications.

关键词： Water resources Spatial databases smart cities Engines Cloud computing Sensors Monitoring

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