@proceedings {Kushwaha2018864, title = {Providing sensor services by data correlation: The $\#$SmartME approach}, journal = {Conference on Complex, Intelligent, and Software Intensive Systems}, volume = {611}, year = {2017}, note = {cited By 0; Conference of 11th International Conference on Complex, Intelligent, and Software Intensive Systems, CISIS 2017 ; Conference Date: 10 July 2017 Through 12 July 2017}, pages = {864-874}, publisher = {Springer Verlag}, address = {Torino, Italy - 10-12 July 2017}, abstract = {

In the current era Internet is the most used medium for sharing and retrieving the information for building applications which are commonly developed for enhancing the user experience in terms of comfort, communication. For this, the need of real-time sensor data gains importance. The data collected from the physical objects should be easily available for different applications. Semantic representation of the sensor data directly addresses the problem of storing it in logical, easily accessible and extensible manner. Our paper works towards converting the already collected sensor data of the $\#$SmartME project into semantic format and also proposes real-time storage of semantically enriched sensor data. To build applications using these sensor data the authors consider mainly three kinds of sensors, i.e., Temperature, Humidity, Pressure. Predicting the observed value of any sensor data is the main aim of this work. The analysis leverages other sensors \& environmental parameters such as Date, Time, Longitude, Latitude, Altitude etc. Correlation among these parameters and the accuracy of the predicted results showed the suitability of our proposed idea. {\textcopyright} Springer International Publishing AG 2018.

}, keywords = {Building applications, Complex networks, Correlations, Data correlations, Data mining, Digital storage, Environmental parameter, Real time sensors, Semantic representation, Semantic Web, sensor networks, SmartME, Stack4Things}, isbn = {9783319615653}, issn = {21945357}, doi = {10.1007/978-3-319-61566-0_82}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85026317817\&doi=10.1007\%2f978-3-319-61566-0_82\&partnerID=40\&md5=7b4cb65c4b09ea03df77bbea893f4002}, author = {Nidhi Kushwaha and Giovanni Merlino and Francesco Longo and Dario Bruneo and Antonio Puliafito and O.P. Vyas} } @proceedings {7210305, title = {An integrated system for advanced water risk management based on cloud computing and IoT}, journal = {2nd World Symposium on Web Applications and Networking (WSWAN)}, year = {2015}, month = {March}, pages = {1-7}, publisher = {IEEE Computer Society}, abstract = {

Nowadays, the research and industrial communities are focusing their efforts on the adoption of Cloud computing for a massive interaction with the physical environment. At the same time the concept of Internet of Things (IoT), in which several embedded systems are interconnected over the Internet, is becoming more and more popular. In this context, the SIGMA project aims to exploit Cloud technologies to collect, integrate, and process heterogeneous pieces of data coming from different wireless sensor networks (e.g., meteorological, seismic, and water observatories) with the purpose to build a distributed risk management system for controlling and monitoring both environmental and industrial risks for people and things. In this paper, we specifically discuss on how SIGMA enables users to manage risks related to water. In particular, we will discuss how the whole SIGMA stack works describing the whole process from the moment in which water sensed data (e.g., turbidity, speed, methane, dissolved oxygen, water level, etc) are collected from heterogeneous sensor networks to the moment in which the Cloud-based system uniforms and stores them for processing.

}, keywords = {advanced water risk management, cloud computing, distributed risk management system, embedded systems, Floods, Internet of Things, IoT, Metals, meteorological observatories, physical environment, Risk management, Rivers, seismic observatories, sensor networks, SIGMA project, Transducers, water observatories, Water pollution, Water resources, Wireless sensor networks}, doi = {10.1109/WSWAN.2015.7210305}, url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true\&arnumber=7210305}, author = {Haijiang Tai and Celesti, A. and Fazio, M. and Villari, M. and Puliafito, A.} } @booklet {253, title = {Energy Management in Industrial Plants}, journal = {COMPUTERS}, volume = {1}, year = {2012}, pages = {24{\textendash}40}, abstract = {The Smart Grid vision imposes a new approach towards energy supply that is more affordable, reliable and sustainable. The core of this new vision is the use of advanced technology to monitor power system dynamics in real time and identify system in stability. In order to implement strategic vision for energy management, it is possible to identify three main areas of investigation such as smart generation, smart grid and smart customer. Focusing on the latter topic, in this paper we present an application specifically designed to monitor an industrial site with particular attention to power consumption. This solution is a real time analysis tool, able to produce useful results to have a strategic approach in the energy market and to provide statistic analysis useful for the future choices of the industrial company. The application is based on a three layers architecture. The technological layer uses a Wireless Sensor Network (WSN) to acquire data from the electrical substations. The middleware layer faces the integration problems by processing the raw data. The application layer manages the data acquired from the sensors. This WSN based architecture represents an interesting example of a low cost and non-invasive monitoring application to keep the energy consumption of an industrial site under control. Some of the added value features of the proposed solution are the routing network protocol, selected in order to have an high availability of the WSN, and the use of the WhereX middleware, able to easily implement integration among the different architectural parts.}, keywords = {middleware, monitoring tool, routing protocols, sensor networks}, doi = {10.3390/computers1010024}, author = {Bruneo D and Cucinotta A and Longo A and Puliafito A and Scarpa M} } @proceedings {257, title = {Monitoring Energy Consumption in an Industrial Site}, journal = {Advances in Computer, Communication, Control and Automation}, volume = {121}, year = {2011}, month = {20, 2011}, pages = {53{\textendash}60}, publisher = {Springer}, address = {Heidelberg}, abstract = {

The Smart Grid vision imposes a new approach towards energy supply that is more affordable, reliable and sustainable. The core of this new vision is the use of advanced technology to monitor power system dynamics in real time and identify system in stability. In this pa-per we present a real time analysis tool specifically designed to monitor an industrial site with particular attention to power consumption. This solution, based on Wireless Sensor Networks, is able to produce useful results and to provide statistic analysis useful for the future choices of the industrial company.

}, keywords = {middleware., routing protocols, sensor networks}, author = {Bruneo D. and Cucinotta A. and Longo Minnolo A. and Puliafito A. and Scarpa A.} } @proceedings {Bruneo2010, title = {Reliability assessment of wireless sensor nodes with non-linear battery discharge}, journal = {2010 IFIP Wireless Days, WD 2010}, year = {2010}, note = {cited By 8; Conference of 2010 IFIP Wireless Days, WD 2010 ; Conference Date: 20 October 2010 Through 22 October 2010; Conference Code:83354}, publisher = {IEEE Computer Society}, address = {Venice, Italy, 20-22 October 2010}, abstract = {

Wireless sensor networks are constituted of a large number of tiny sensor nodes randomly distributed over a geographical region. In order to reduce power consumption, nodes undergo cycles of active-sleep periods that reduce their ability to send/receive data. Aim of this paper is to analyze the reliability of a battery-powered sensor node with active-sleep cycles considering both linear and non linear discharge processes. The approach used in the evaluation is based on continuous phase type distributions and Kronecker algebra. The technique is thus applied to the evaluation of an example in order to demonstrate its effectiveness. The obtained results strongly encourage future work, figuring out possible application in wider network context with complex topology, redundant nodes, and unreliable links, due to the Kronecher algebra capabilities to manage the state space explosion problem. {\textcopyright} 2010 IEEE.

}, keywords = {Algebra, Battery discharge, Continuous phase, Electric network synthesis, Energy consumption, Energy utilization, Kronecker algebra, Markov reward model, Reliability analysis, sensor networks, Sensor nodes, Telecommunication equipment, Wireless sensor, Wireless sensor networks}, isbn = {9781424492299}, doi = {10.1109/WD.2010.5657711}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-78751474054\&partnerID=40\&md5=86f6f2fa864d7e52672ab4e4bd83d78a}, author = {Dario Bruneo and Salvatore Distefano and Francesco Longo and Antonio Puliafito and Marco Scarpa} }