Big Sensor Data Systems for Smart Cities

Recent advances in large-scale networked sensor technologies and the explosive growth in big data computing have made it possible for new application deployments in smart cities ecosystems. In this paper, we define big sensor data systems, and survey progress made in the development and applications of big sensor data research. We classify the existing research based on their characteristics and smart city layer challenges. Next, we discuss several applications for big sensor data systems, and explore the potential of large-scale networked sensor technologies for smart cities in the big data era. We conclude this paper by discussing future work directions highlighting some futuristic applications. The aim of this survey paper is to be useful for researchers to get insights into this important area, and motivate the development of practical solutions toward deployment in smart cities.

[1]  Yasar Guneri Sahin,et al.  Animals as Mobile Biological Sensors for Forest Fire Detection , 2007, Sensors.

[2]  Catherine Rosenberg,et al.  Compressed Data Aggregation: Energy-Efficient and High-Fidelity Data Collection , 2013, IEEE/ACM Transactions on Networking.

[3]  Victor C. M. Leung,et al.  Mobility Support for Health Monitoring at Home Using Wearable Sensors , 2011, IEEE Transactions on Information Technology in Biomedicine.

[4]  Sajal K. Das,et al.  A novel localization and coverage framework for real-time participatory urban monitoring , 2015, Pervasive Mob. Comput..

[5]  Lida Xu,et al.  An Integrated System for Regional Environmental Monitoring and Management Based on Internet of Things , 2014, IEEE Transactions on Industrial Informatics.

[6]  J. Li,et al.  Smart city and the applications , 2011, 2011 International Conference on Electronics, Communications and Control (ICECC).

[7]  Sanjay Kumar Madria,et al.  Risk Assessment in a Sensor Cloud Framework Using Attack Graphs , 2017, IEEE Transactions on Services Computing.

[8]  G. Bianchi,et al.  Opportunistic communication in smart city: Experimental insight with small-scale taxi fleets as data carriers , 2016, Ad Hoc Networks.

[9]  Michael Grossniklaus,et al.  Situation monitoring of urban areas using social media data streams , 2016, Inf. Syst..

[10]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.

[11]  Christine Louise Outram,et al.  The Copenhagen Wheel: An innovative electric bicycle system that harnesses the power of real-time information and crowd sourcing , 2010 .

[12]  Xuan Song,et al.  Intelligent System for Human Behavior Analysis and Reasoning Following Large-Scale Disasters , 2013, IEEE Intelligent Systems.

[13]  J. Wareham,et al.  A Smart City Initiative: the Case of Barcelona , 2012, Journal of the Knowledge Economy.

[14]  Athanasios V. Vasilakos,et al.  Big data analytics: a survey , 2015, Journal of Big Data.

[15]  Margaret Martonosi,et al.  ON CELLULAR , 2022 .

[16]  Rajkumar Buyya,et al.  Article in Press Future Generation Computer Systems ( ) – Future Generation Computer Systems Cloud Computing and Emerging It Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility , 2022 .

[17]  Shreyas Sen,et al.  Invited: Context-aware energy-efficient communication for IoT sensor nodes , 2016, 2016 53nd ACM/EDAC/IEEE Design Automation Conference (DAC).

[18]  Ian J. Wassell,et al.  Energy-efficient signal acquisition in wireless sensor networks: a compressive sensing framework , 2012, IET Wirel. Sens. Syst..

[19]  Kirsten Halsnæs,et al.  Definition of Smart Energy City and State of the art of 6 Transform cities using Key Performance Indicators: Deliverable 1.2 , 2013 .

[20]  Desheng Zhang,et al.  A Carpooling Recommendation System for Taxicab Services , 2014, IEEE Transactions on Emerging Topics in Computing.

[21]  Alexa Huth,et al.  The Basics of Cloud Computing , 2011 .

[22]  Konstantinos Psounis,et al.  Modeling spatially correlated data in sensor networks , 2006, TOSN.

[23]  Bart De Moor,et al.  Kernel-based Data Fusion for Machine Learning - Methods and Applications in Bioinformatics and Text Mining , 2009, Studies in Computational Intelligence.

[24]  Rick Cattell,et al.  Scalable SQL and NoSQL data stores , 2011, SGMD.

[25]  Hui Xiong,et al.  Cross-Domain Learning from Multiple Sources: A Consensus Regularization Perspective , 2010, IEEE Transactions on Knowledge and Data Engineering.

[26]  Antonio Iera,et al.  The Internet of Things: A survey , 2010, Comput. Networks.

[27]  Carlo Ratti,et al.  Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome , 2011, IEEE Transactions on Intelligent Transportation Systems.

[28]  Josep Blat,et al.  Digital Footprinting: Uncovering Tourists with User-Generated Content , 2008, IEEE Pervasive Computing.

[29]  David Gil,et al.  Internet of Things: A Review of Surveys Based on Context Aware Intelligent Services , 2016, Sensors.

[30]  Xiaoyong Du,et al.  Big data challenge: a data management perspective , 2013, Frontiers of Computer Science.

[31]  Sanjay Madria,et al.  Sensor Cloud: A Cloud of Virtual Sensors , 2014, IEEE Software.

[32]  Wei-Ying Ma,et al.  A Cloud-Based Knowledge Discovery System for Monitoring Fine-Grained Air Quality , 2014 .

[33]  Yonggang Wen,et al.  Toward Scalable Systems for Big Data Analytics: A Technology Tutorial , 2014, IEEE Access.

[34]  Christina Freytag,et al.  The Definitive Guide To Mongodb The Nosql Database For Cloud And Desktop Computing , 2016 .

[35]  Yunpeng Wang,et al.  Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory , 2015, PloS one.

[36]  Vivek Sehgal,et al.  1 SensoClean : Handling Noisy and Incomplete Data in Sensor Networks using Modeling , 2005 .

[37]  Jon E. Froehlich,et al.  Measuring the Pulse of the City through Shared Bicycle Programs , 2008 .

[38]  Carlo Ratti,et al.  Enabling the Real-Time City: LIVE Singapore! , 2012 .

[39]  Jameela Al-Jaroodi,et al.  Applications of big data to smart cities , 2015, Journal of Internet Services and Applications.

[40]  Diane J. Cook,et al.  Activity Recognition Based on Home to Home Transfer Learning , 2010, Plan, Activity, and Intent Recognition.

[41]  Yu Zheng,et al.  U-Air: when urban air quality inference meets big data , 2013, KDD.

[42]  M. Shamim Hossain,et al.  A Survey on Sensor-Cloud: Architecture, Applications, and Approaches , 2013, Int. J. Distributed Sens. Networks.

[43]  Chunming Rong,et al.  K-means Clustering in the Cloud -- A Mahout Test , 2011, 2011 IEEE Workshops of International Conference on Advanced Information Networking and Applications.

[44]  Hidde Leijnse,et al.  Country-wide rainfall maps from cellular communication networks , 2013, Proceedings of the National Academy of Sciences.

[45]  Lida Xu,et al.  Compressed Sensing Signal and Data Acquisition in Wireless Sensor Networks and Internet of Things , 2013, IEEE Transactions on Industrial Informatics.

[46]  Fiorella Lauro,et al.  Fault detection analysis using data mining techniques for a cluster of smart office buildings , 2015, Expert Syst. Appl..

[47]  Qiang Yang,et al.  Transferring Localization Models across Space , 2008, AAAI.

[48]  Tommi Mikkonen,et al.  From the Internet of Things to the Internet of People , 2015, IEEE Internet Computing.

[49]  Arkady B. Zaslavsky,et al.  Context Aware Computing for The Internet of Things: A Survey , 2013, IEEE Communications Surveys & Tutorials.

[50]  Bhishna Bajracharya,et al.  Challenges and opportunities to develop a smart city: A case study of Gold Coast, Australia , 2014 .

[51]  Neal Leavitt,et al.  Will NoSQL Databases Live Up to Their Promise? , 2010, Computer.

[52]  Hany Assasa,et al.  Service Mobility in Mobile Networks , 2015, 2015 IEEE 8th International Conference on Cloud Computing.

[53]  C. L. Philip Chen,et al.  Data-intensive applications, challenges, techniques and technologies: A survey on Big Data , 2014, Inf. Sci..

[54]  Anthony Stefanidis,et al.  #Earthquake: Twitter as a Distributed Sensor System , 2013, Trans. GIS.

[55]  Nirvana Meratnia,et al.  Sensing Solutions for Collecting Spatio-Temporal Data for Wildlife Monitoring Applications: A Review , 2013, Sensors.

[56]  Jignesh M. Patel,et al.  Big data and its technical challenges , 2014, CACM.

[57]  Xiong Zhang,et al.  Survey of Data-Centric Smart City , 2014 .

[58]  Jui-Sheng Chou,et al.  Smart grid data analytics framework for increasing energy savings in residential buildings , 2016 .

[59]  Fei-Yue Wang,et al.  Traffic Flow Prediction With Big Data: A Deep Learning Approach , 2015, IEEE Transactions on Intelligent Transportation Systems.

[60]  Shrideep Pallickara,et al.  On the performance of high dimensional data clustering and classification algorithms , 2013, Future Gener. Comput. Syst..

[61]  Milind R. Naphade,et al.  Smarter Cities and Their Innovation Challenges , 2011, Computer.

[62]  Yunhao Liu,et al.  Big Data: A Survey , 2014, Mob. Networks Appl..

[63]  Qiang Yang,et al.  Cross-domain activity recognition , 2009, UbiComp.

[64]  Chen Feng,et al.  Performance Benefits of DataMPI: A Case Study with BigDataBench , 2014, BPOE@ASPLOS/VLDB.

[65]  Andrea Zanella,et al.  Internet of Things for Smart Cities , 2014, IEEE Internet of Things Journal.

[66]  M. Angelidou Smart cities: A conjuncture of four forces , 2015 .

[67]  Rong Luo,et al.  An accurate and low-cost PM2.5 estimation method based on Artificial Neural Network , 2015, The 20th Asia and South Pacific Design Automation Conference.

[68]  Betul Karakus,et al.  Architecture and Implementation of a Scalable Sensor Data Storage and Analysis System Using Cloud Computing and Big Data Technologies , 2015, J. Sensors.

[69]  Lavanya Ramakrishnan,et al.  Performance evaluation of a MongoDB and hadoop platform for scientific data analysis , 2013, Science Cloud '13.

[70]  Ian H. Witten,et al.  WEKA: a machine learning workbench , 1994, Proceedings of ANZIIS '94 - Australian New Zealnd Intelligent Information Systems Conference.

[71]  Evangelos Theodoridis,et al.  SmartSantander: IoT experimentation over a smart city testbed , 2014, Comput. Networks.

[72]  R. Kitchin The real-time city? Big data and smart urbanism , 2013 .

[73]  Hui Wang,et al.  Connectivity, coverage and power consumption in large-scale wireless sensor networks , 2014, Comput. Networks.

[74]  Marimuthu Palaniswami,et al.  Internet of Things (IoT): A vision, architectural elements, and future directions , 2012, Future Gener. Comput. Syst..

[75]  Thomas Blaschke,et al.  Contextual Sensing: Integrating Contextual Information with Human and Technical Geo-Sensor Information for Smart Cities , 2015, Sensors.

[76]  Zhijun Li,et al.  Fine-Grained Air Quality Monitoring Based on Gaussian Process Regression , 2014, ICONIP.

[77]  Deborah Estrin,et al.  Synthetic Data Generation to Support Irregular Sampling in Sensor Networks , 2004 .

[78]  Florin Radulescu,et al.  MongoDB vs Oracle -- Database Comparison , 2012, 2012 Third International Conference on Emerging Intelligent Data and Web Technologies.

[79]  Yi Jin,et al.  Research on the improvement of MongoDB Auto-Sharding in cloud environment , 2012, 2012 7th International Conference on Computer Science & Education (ICCSE).

[80]  Yoshihide Sekimoto,et al.  Large-Scale Auto-GPS Analysis for Discerning Behavior Change during Crisis , 2013, IEEE Intelligent Systems.

[81]  Jinjun Chen,et al.  A Time Efficient Approach for Detecting Errors in Big Sensor Data on Cloud , 2015, IEEE Transactions on Parallel and Distributed Systems.

[82]  Jó Ueyama,et al.  Development of a spatial decision support system for flood risk management in Brazil that combines volunteered geographic information with wireless sensor networks , 2015, Comput. Geosci..

[83]  Claire D'Este,et al.  Distributed Feature Selection with Big Sensor Data , 2014, MLSDA'14.

[84]  José M. F. Moura,et al.  Big Data + Big Cities: Graph Signals of Urban Air Pollution [Exploratory SP] , 2014, IEEE Signal Processing Magazine.

[85]  Lothar Thiele,et al.  Deriving high-resolution urban air pollution maps using mobile sensor nodes , 2015 .

[86]  Brendan Jennings,et al.  Context-awareness and the smart grid: Requirements and challenges , 2015, Comput. Networks.

[87]  Arkady B. Zaslavsky,et al.  Sensing as a service model for smart cities supported by Internet of Things , 2013, Trans. Emerg. Telecommun. Technol..

[88]  Tim Hawkins,et al.  The Definitive Guide to MongoDB: The NoSQL Database for Cloud and Desktop Computing , 2010 .

[89]  Kah Phooi Seng,et al.  Termite-hill: Performance optimized swarm intelligence based routing algorithm for wireless sensor networks , 2012, J. Netw. Comput. Appl..