A Service Based Architecture for Multidisciplinary IoT Experiments with Crowdsourced Resources

Research on emerging networking paradigms, such as Mobile Crowdsensing Systems, requires new types of experiments to be conducted and an increasing spectrum of devices to be supported by experimenting facilities. In this work, we present a service based architecture for IoT testbeds which (a) exposes the operations of a testbed as services by following the Testbed as a Service (TBaaS) paradigm; (b) enables diverse facilities to be federated in a scalable and standardized way and (c) enables the seamless integration of crowdsourced resources (e.g. smartphones and wearables) and their abstraction as regular IoT resources. The architecture enables an experimenter to access a diverse set of resources and orchestrate experiments via a common interface by hiding the underlying heterogeneity and complexity. This way, the field of IoT experimentation with real resources is further promoted and broadened to also address researchers from other fields and discipline

Modelled testbeds: Visualizing and augmenting physical testbeds with virtual resources

Testbed facilities play a major role in the study and evolution of emerging technologies, such as those related to the Internet of Things. In this work we introduce the concept of modelled testbeds, which are 3D interactive representations of physical testbeds where the addition of virtual resources mimicking the physical ones is made possible thanks to back-end infrastructure. We present the architecture of the Syndesi testbed, deployed at the premises of University of Geneva, which was used for the prototype modelled testbed. We investigate several extrapolation techniques towards realistic value assignment for virtual sensor measurements. K-fold cross validation is performed in a dataset comprising of nearly 300’000 measurements of temperature, illuminance and humidity sensors collected from the physical sensors of the Syndesi testbed, in order to evaluate the accuracy of the methods. We obtain strong results including Mean Absolute Percentage Error (MAPE) levels below 7%

Advancing experimentation-as-a-service through urban IoT experiments

Smart cities are becoming a vibrant application domain for a number of science fields. As such, service providers and stakeholders are beginning to integrate co-creation aspects into current implementations to shape the future smart city solutions. In this context, holistic solutions are required to test such aspects in real city-scale Internet of Things (IoT) deployments, considering the complex city ecosystems. In this paper, we discuss OrganiCity's implementation of an experimentation-as-a-service (EaaS) framework, presenting a toolset that allows developing, deploying, and evaluating smart city solutions in a one-stop shop manner. This is the first time such an integrated toolset is offered in the context of a large-scale IoT infrastructure, which spans across multiple European cities. We discuss the design and implementation of the toolset, presenting our view on what EaaS should provide, and how it is implemented. We present initial feedback from 25 experimenter teams that have utilized this toolset in the OrganiCity project, along with a discussion on two detailed actual use cases to validate our approach. Learnings from all experiments are discussed as well as architectural considerations for platform scaling. Our feedback from experimenters indicates that EaaS is a viable and useful approach.The authors would like to thank the experimenter teams and volunteers who participated in OrganiCit

Smart city : How smart is it actually?

The global megatrends of population growth and fast urbanisation are negatively impacting the life in the cities. Smart city is the high-level concept by which the cities try to address the need to improve their social, economic and environmental sustainability. This thesis studies how the smart city concept is defined, what are the underlying hypotheses and assumptions on which the smart city research is based on, what are the latest results and innovations of the smart city research, how the smart city initiatives are meeting their objectives, and how the hypotheses and assumptions may vary between the smart city initiatives. The objective of this study is to critically review the smart city research paradigm to find possible pitfalls, conflicting results and topics for further study and improvement. This research is conducted as a traditional critical literature review, covering the current academic literature on the smart city topic, the websites presenting the smart city initiatives around the world, and the latest popular literature for contrasting views. A qualitative comparison of the smart city initiatives in selected cities – Helsinki, Singapore and London – complements the literature review. The research strategy in this study approximates the grounded theory, utilising inductive reasoning to generate arguments and conclusions about the form, validity and future of the smart city. This study produced the following key findings: there are many different and overlapping definitions of smart city; the smart city development is mostly seen as the responsibility of smart ICT implementations, while simultaneously demanding for a more focused human viewpoint; the smart city initiatives form complex, multidisciplinary platforms that require holistic evaluation; the current evaluation methods and rankings of the smart cities vary considerably, making the evaluation of the success of the smart cities difficult; some of the existing smart city elements and proposed solutions are ineffective or even counterproductive for the smart city objectives. The main conclusions of this study were that the complex nature of the smart city initiatives and the conflicts and interdependencies of the smart city objectives are not fully addressed in the current smart city research, and that the current smart city research is not adequately multidisciplinary in nature. For the future, this research argues for the increased utilisation of research methods used in information systems science for their ability to address socio-technical and multidisciplinary problems. Also, the need for a future research on the efficacy of the multidisciplinary research of smart cities is identified.Väestönkasvu, siitä aiheutuva muuttoliike ja nopea kaupungistuminen ovat maailmanlaajuisia megatrendejä, jotka usein vaikuttavat kielteisesti elämisen ja asumisen laatuun kaupungeissa. Älykaupunki on ylemmän tason konsepti, jonka avulla kaupungit yrittävät muokata sosiaalista, taloudellista ja ympäristönsä kehitystä kestävämmälle pohjalle. Tässä tutkielmassa tarkastellaan, miten älykaupungin konsepti on määritelty, mitkä ovat ne taustaolettamukset ja perusteet, joiden varaan älykaupunkien tieteellinen tutkimus pohjautuu, mitkä ovat älykaupunkitutkimuksen viimeisimmät tulokset ja innovaatiot, miten älykaupunkihankkeet saavuttavat tavoitteensa ja miten niiden perusteet ja taustaolettamukset vaihtelevat älykaupunkien välillä. Tämän tutkimuksen tavoitteena on kriittisesti tarkastella älykaupunkien tutkimusparadigmaa ja löytää mahdollisia sudenkuoppia sekä ristiriitaisia tutkimusaiheita ja -tuloksia, joita voitaisiin käyttää älykaupunkien jatkotutkimukseen ja -kehittämiseen tulevaisuudessa. Tämä tutkimus on toteutettu perinteisenä kriittisenä kirjallisuustutkimuksena. Lähdeaineistona on käytetty älykaupunkien viimeisimpiä akateemisia tutkimustuloksia ja julkaisuja, älykaupunkihankkeiden omia nettisivustoja ympäri maailman sekä kontrastin vuoksi myös viimeisimpiä populaarin lähdekirjallisuuden käsittelemiä aiheita ja ilmiöitä. Kirjallisuustutkimusta on täydennetty kvalitatiivisella älykaupunkivertailulla, jossa Helsingin, Singaporen ja Lontoon älykaupunkihankkeita on vertailtu keskenään. Työn tutkimusstrategia muistuttaa ankkuroitua teoriaa, jossa induktiivisen päättelyn avulla pyritään lähdeaineistosta löytämään ja luomaan väitteitä, perusteluja ja johtopäätöksiä älykaupunkien muodosta, olemassaolon oikeellisuudesta ja tulevaisuudesta. Tutkimuksessa havaittiin seuraavat pääkohdat: älykaupunki voidaan määritellä usealla, myöskin samanaikaisesti päällekkäisellä tavalla; älykaupunkien kehittäminen nähdään yleensä tieto- ja viestintäteknologisten innovaatioiden kehittämisenä, vaikka samanaikaisesti usein vaaditaan myös inhimillisemmän näkökulman korostamista; älykaupunkihankkeet muodostavat monitahoisia, monia tieteenaloja koskettavia alustoja, jotka vaativat nykyistä kokonaisvaltaisempaa tarkastelua ja arvi-ointia; nykyiset älykaupunkien menestyksen mittarit ja arviointitavat vaihtelevat huomattavasti, jolloin älykaupunkien älykkyyden ja onnistumisen yhteismitallinen arviointi on vaikeaa; jotkut havaituista älykaupunkien ominaisuuksista ja ratkaisuista ovat tehottomia tai jopa kielteisesti älykaupunkien tavoitteisiin vaikuttavia. Tässä tutkimuksessa päädyttiin seuraaviin johtopäätöksiin: älykaupunkihankkeiden monimutkaisen ja ristiriitaisen luonteen takia nykyinen älykaupunkitutkimus- ja kehitys ei täysin pysty vastaamaan näiden ristiriitaisuuksien ja keskinäisriippuvuuksien tuomiin haasteisiin; nykyinen älykaupunkitutkimus ei myöskään ole tieteellisesti riittävän monialaista. Tämän tutkimuksen pohjalta voidaan suositella, että tulevaisuudessa älykaupunkien kehitys voisi pohjautua enemmän tietojärjestelmätieteiden tutkimusmetodologioiden hyödyntämiseen, jolloin älykaupunkien vaatimat sosiotekniset ja monitieteelliset näkökulmat saataisiin paremmin havaittua, katettua ja arvioitua tutkimustuloksissa. Tulevaisuudessa tarvitaan myös tutkimusta siitä, kuinka tehokkaasti monitieteellinen älykaupunkitutkimus onnistuu

Managing pervasive sensing campaigns via an experimentation-as-a-service platform for smart cities

The adoption of technologies like the IoT in urban environments, together with the intensive use of smartphones, is driving transformation towards smart cities. Under this perspective, Experimentation-as-a-Service within OrganiCity aims to create an experimental facility with technologies, services, and applications that simplify innovation within urban ecosystems. We discuss here tools that facilitate experimentation, implementing ways to organize, execute, and administer experimentation campaigns in a smart city context. We discuss the benefits of our framework, presenting some preliminary results. This is the first time such tools are paired with large-scale smart city infrastructures, enabling both city-scale experimentation and cross-site experimentation.This work was partially supported by the OrganiCity research project funded by the European Union, under the grant agreement No. 645198 of the Horizon 2020 research and innovation progra

Earth Observation Open Science and Innovation

geospatial analytics; social observatory; big earth data; open data; citizen science; open innovation; earth system science; crowdsourced geospatial data; citizen science; science in society; data scienc

PLATFORM-DRIVEN CROWDSOURCED MANUFACTURING FOR MANUFACTURING AS A SERVICE

Platform-driven crowdsourced manufacturing is an emerging manufacturing paradigm to instantiate the adoption of the open business model in the context of achieving Manufacturing-as-a-Service (MaaS). It has attracted attention from both industries and academia as a powerful way of searching for manufacturing solutions extensively in a smart manufacturing era. In this regard, this work examines the origination and evolution of the open business model and highlights the trends towards platform-driven crowdsourced manufacturing as a solution for MaaS. Platform-driven crowdsourced manufacturing has a full function of value capturing, creation, and delivery approach, which is fulfilled by the cooperation among manufacturers, open innovators, and platforms. The platform-driven crowdsourced manufacturing workflow is proposed to organize these three decision agents by specifying the domains and interactions, following a functional, behavioral, and structural mapping model. A MaaS reference model is proposed to outline the critical functions and inter-relationships. A series of quantitative, qualitative, and computational solutions are developed for fulfilling the outlined functions. The case studies demonstrate the proposed methodologies and can pace the way towards a service-oriented product fulfillment process. This dissertation initially proposes a manufacturing theory and decision models by integrating manufacturer crowds through a cyber platform. This dissertation reveals the elementary conceptual framework based on stakeholder analysis, including dichotomy analysis of industrial applicability, decision agent identification, workflow, and holistic framework of platform-driven crowdsourced manufacturing. Three stakeholders require three essential service fields, and their cooperation requires an information service system as a kernel. These essential functions include contracting evaluation services for open innovators, manufacturers' task execution services, and platforms' management services. This research tackles these research challenges to provide a technology implementation roadmap and transition guidebook for industries towards crowdsourcing.Ph.D