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Proactive Adaptation of Behavior for Smart Connected ObjectsFejzo, Orsola January 2019 (has links)
The great amount of generated data from IoT infrastructures in Smart Cities, if properly leveraged, presents the opportunity to shift towards more sustainable practices in rapidly increasing urban areas. Reasoning upon this data in a proactive way, by avoiding unwanted future events before they occur, leads to more efficient services. For a system to do so, a robust reasoning model, able to anticipate upcoming events and pick the most suitable adaptation option is needed. Recently deployed smart waste management systems for monitoring and planning purposes report substantial cost-savings and carbon footprint reductions, however, such systems can be further enhanced by integrating proactive capabilities. This work proposes a novel reasoning model and system architecture called ProAdaWM for more effective and efficient waste operations when faced with severe weather events. A Bayesian Network and Utility Theory, as the basis of Decision Theory, are utilized to model the uncertainties and handle how the system adapts; the proposed model utilizes weather information and data from bin level sensor for reasoning. The approach is validated through the implementation of a prototype and the conduction of a case study; the results demonstrate the expected behavior.
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Organizational adaptation towards artificial intelligence : A case study at a public organization / Organisatorisk anpassning till artificiell intelligens : En fallstudie i en offentlig organisationFredriksson, Sofia January 2018 (has links)
Artificiell intelligens har blivit kommersialiserad och har skapat en stor efterfrågan på marknaden. Trots detta är det få som vet vad teknologin innebär och till och med forskare kämpar med att hitta en universell definition. Teknologin är komplex och mångfacetterad och delar av tekniken gör den kontroversiell. Artificiell intelligens som koncept har blivit studerat utifrån ett tekniskt perspektiv och flera publikationer har gjort ett försökt att förutspå hur teknologin kommer att påverka samhällen i framtiden. Även fast efterfrågan är stor, saknas det empiriska data för hur tekniken påverkar organisationer. Det finns därför ingen nuvarande forskning till hjälp för organisationer som måste anpassa sig till teknologin.Syftet med denna studie är att börja täcka detta forskningsgap med empiriska data för att hjälpa organisationer förstå hur de påverkas av detta paradigmskifte i teknik. Studien är utförd som en fallstudie vid en offentlig organisation med medel teknologiska kunskaper. Data har samlats in via intervjuer, observationer och granskning av styrdokument. Sjutton intervjuer hölls med medarbetare från olika delar av organisationen. Data analyserades sedan utifrån ett kombinerat ramverk inkluderande teknik, organisatorisk anpassning och social hållbarhet.Studien visade att organisationen är reaktiv i sin anpassningsprocess och saknar en förståelse för tekniken. Resultatet visar att konceptet artificiell intelligens är svårt att förstå men tillämpbara exempel underlättar processen. Ett bättre informationsflöde skulle hjälpa organisationen att bli mer proaktiv i sin anpassning och bättre kunna utnyttja sin personal. Resultaten visar också att det finns etiska aspekter kring teknologin som behöver behandlas av organisationen innan artificiell intelligens kan implementeras. Forskaren argumenterar också för vikten av att använda ett sammansatt ramverk vid analys av organisatorisk påverkan av artificiell intelligens på grund av dess komplexitet. / Artificial intelligence has become commercialized and has created a huge demand on the market. However, few people know what the technology means and even scientist struggle to find a universal definition. The technology is complex and versatile with elements making it controversial. The concept of artificial intelligence has been studied in the technical field and several publications has made efforts to predict the impact that the technology will have on our societies in the future. Even if the technology has created a great demand on the market, empirical findings of how this technology is affecting organizations is lacking. There is thus no current research to help organizations adapt to this new technology.The purpose of this study is to start cover that research gap with empirical data to help organizations understand how they are affected by this paradigm shift in technology. The study is conducted as a single case study at a public organization with middle technological skills. Data has been collected through interviews, observations and reviewing of governing documents. Seventeen interviews were held with employees with different work roles in the administration. The data was then analyzed from a combined framework including technology, organizational adaptation and social sustainability.The study found that the organization is reactive in its adaptation process and lacking an understanding of the technology. The findings show that the concept of artificial intelligence is hard to understand but applicable and tangible examples facilitates the process. A better information flow would help the investigated organization to become more proactive in its adaptation and better utilize its personnel. The findings also show that there are ethical issues about the technology that the organization needs to process before beginning an implementation. The researcher also argues the importance of a joint framework when analyzing the organizational impact of artificial intelligence due to its complexity.
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