A Linked Data-Based Semantic Information Model for Smart Cities
Smart cities typically involve a myriad of interconnected systems intended to promote better management of urban and natural resources of cities, thereby contributing to the improve the quality of life of citizens. The heterogeneity of domains, systems, data, and relationships among them requires defining a data model able to express information in a flexible, extensible way while promoting interoperability between systems and applications. Furthermore, smart city systems can benefit from georeferenced information to allow for more effective actions over the real-world urban space. Aiming at tackling challenges related to data heterogeneity while considering georeferenced information, this work introduces LGeoSIM, a semantic-based information model for smart cities as means of fostering interoperability and powerful automated reasoning upon unambiguous information. LGeoSIM relies on the recent NGSI-LD Specification, thereby encompassing the principles of Linked Data to allow semantically defining information through ontologies and their interconnection. This paper also presents an implementation of LGeoSIM within Smart Geo Layers, a geographic-layered data middleware platform conceived to integrate data provided by heterogeneous sources in a smart city environment.
E. Cavalcante N. Cacho F. Lopes T. Batista "Challenges to the development of smart city systems: A system-of-systems view" Proceedings of the 31st Brazilian Symposium on Software Engineering pp. 244-249 2017.
S. Consoli et al. "A smart city data model based on semantics best practice and principles" Proceedings of the 24th International Conference on World Wide Web pp. 1395-1400 2015.
N. Komninos C. Bratsas C. Kakderi P. Tsarchopoulos "Smart city ontologies: Improving the effectiveness of smart city applications" Journal of Smart Cities vol. 1 no. 1 pp. 1-16 2015.
T. Heath C. Bizer Linked Data: Evolving the Web into a global data space Morgan & Claypool Publishers 2011.
M. d’Aquin J. Davies E. Motta "Smart cities’ data: Challenges and opportunities for semantic technologies" IEEE Internet Computing vol. 19 no. 6 pp. 66-70 Nov.–Dec. 2015.
A. Souza et al. "A geographic-layered data middleware for smart cities" Proceedings of the 24th Brazilian Symposium on Multimedia and the Web pp. 411-414 2018.
A. De Nicola M. Melchiori M. L. Villania "Creative design of emergency management scenarios driven by semantics: An application to smart cities" Information Systems vol. 81 pp. 21-48 Mar. 2019.
F. Mata et al. "A mobile information system based on crowd-sensed and official crime data for finding safe routes: A case study of Mexico City" Mobile Information Systems vol. 2016 2016.
P. Bellini M. Benigni R. Billero P. Nesi N. Rauch "Km4City ontology building vs data harvesting and cleaning for smart-city services" Journal of Visual Languages & Computing vol. 25 no. 6 pp. 827-839 Dec. 2014.
C. Badii P. Bellini D. Cenni A. Difino P. Nesi M. Paolucci "Analysis and assessment of a knowledge based smart city architecture providing service APIs" Future Generation Computer Systems vol. 75 pp. 14-29 Oct. 2017.
L. Otero-Cerdeira F. J. Rodríguez-Martnez A. Gómez-Rodríguez "Definition of an ontology matching algorithm for context integration in smart cities" Sensors vol. 14 no. 12 pp. 23 581-23 619 2014.
M. Ryu J. Kim J. Yun "Integrated semantics service platform for the Internet of Things: A case study of a smart office" Sensors vol. 15 no. 1 pp. 2137-2160 Jan. 2015.
P. Espinoza-Arias M. Poveda-Villalón R. García-Castro O. Corcho "Ontological representation of smart city data: From devices to cities" Applied Sciences vol. 9 no. 1 Dec. 2018.
C. Perera A. Zaslavsky P. Christen D. Georgakopoulos "Sensing as a Service model for smart cities supported by Internet of Things" Transactions on Emerging Telecommunications Technologies vol. 25 no. 1 pp. 81-93 Jan. 2014.
N. F. Noy D. L. Mcguinness "Ontology Development 101: A guide to creating your first ontology" Tech. Rep. 2001.
S. S. Haykin et al. Neural networks and learning machines/Simon Haykin New York:Prentice Hall 2009.
Y. Li Y. Yuan "Convergence analysis of two-layer neural networks with relu activation" Advances in Neural Information Processing Systems pp. 597-607 2017.
P. Sibi S. A. Jones P. Siddarth "Analysis of different activation functions using back propagation neural networks" Journal of Theoretical and Applied Information Technology vol. 47 no. 3 pp. 1264-1268 2013.
A. S. Ros F. Doshi-Veleza "Improving the adversarial robustness and interpretability of deep neural networks by regularizing their input gradients" in AAAI18 - Humans and AI AAAI pp. 1660-1669 2018.
M. Y. R. Gadelha F. R. Monteiro J. Morse L. C. Cordeiro B. Fischer D. A. Nicole "ESBMC 5.0: an industrial-strength C model checker" in ASE ACM pp. 888-891 2018.
V. Kahlon C. Wang A. Gupta "Monotonic partial order reduction: An optimal symbolic partial order reduction technique" CAV ser. LNCS vol. 5643 pp. 398-413 2009.
A. Betts N. Chong A. F. Donaldson S. Qadeer P. Thomson "Gpuverify: a verifier for GPU kernels" OOPSLA pp. 113-132 2012.
M. Krichen S. Tripakis "Conformance testing for real-time systems" Formal Methods in System Design vol. 34 no. 3 pp. 238-304 2009.
K. J. Hayhurst A practical tutorial on modified condition/decision coverage DIANE Publishing vol. 210876 2001.
C. Barrett A. Stump C. Tinelli S. Boehme D. Cok D. Deharbe B. Dutertre P. Fontaine V. Ganesh A. Griggio J. Grundy P. Jackson A. Oliveras S. Krsti? M. Moskal L. De Moura R. Sebastiani T. D. Cok J. Hoenicke "The SMT-LIB Standard: Version 2.0" Tech. Rep. 2010.
L. C. Cordeiro B. Fischer J. Marques-Silva "Smt-based bounded model checking for embedded ANSI-C software" IEEE Trans. Software Eng. vol. 38 no. 4 pp. 957-974 2012.
D. Amodei C. Olah J. Steinhardt P. Christiano J. Schulman D. Mané "Concrete problems in ai safety" 2016.
D. Gopinath A. Taly H. Converse C. S. Pasareanu "Finding invariants in deep neural networks" CoRR vol. abs/1904.13215 2019 [online] Available: http://arxiv.org/abs/1904.13215.
D. Gopinath G. Katz C. S. Pasareanu C. W. Barrett "Deepsafe: A data-driven approach for checking adversarial robustness in neural networks" CoRR vol. abs/1710.00486 2017 [online] Available: http://arxiv.org/abs/1710.00486.
G. Li P. Li G. Sawaya G. Gopalakrishnan I. Ghosh S. P. Rajan "GKLEE: concolic verification and test generation for gpus" PPOPP pp. 215-224 2012.
M. Zheng M. S. Rogers Z. Luo M. B. Dwyer S. F. Siegel "CIVL: formal verification of parallel programs" ASE pp. 830-835 2015.
H. Xiao K. Rasul R. Vollgraf "Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms" CoRR vol. abs/1708.07747 2017 [online] Available: http://arxiv.org/abs/1708.07747.
A. Krizhevsky V. Nair G. Hinton The cifar-10 dataset vol. 55 2014 [online] Available: http://www.cs.toronto.edu/kriz/cifar.html.
M. Y. R. Gadelha F. R. Monteiro L. C. Cordeiro D. A. Nicole "ESBMC v6.0: Verifying C programs using k-induction and invariant inference - (competition contribution)" TACAS ser. LNCS vol. 11429 pp. 209-213 2019.
E. H. da S. Alves L. C. Cordeiro E. B. de Lima Filho "A method to localize faults in concurrent C programs" Journal of Systems and Software vol. 132 pp. 336-352 2017.