The Power of Patents: Leveraging Text Mining and Social Network Analysis to Forecast IoT Trends

Technology has become an indispensable competitive tool as science and technology have progressed throughout history. Organizations can compete on an equal footing by implementing technology appropriately. Technology trends or technology lifecycles begin during the initiation phase. Finally, it reaches saturation after entering the maturity phase. As technology reaches saturation, it will be removed or replaced by another. This makes investing in technologies during this phase unjustifiable. Technology forecasting is a critical tool for research and development to determine the future direction of technology. Based on registered patents, this study examined the trends of IOT technologies. A total of 3697 patents related to the Internet of Things from the last six years of patenting have been gathered using lens.org for this purpose. The main people and companies were identified through the creation of the IOT patent registration cooperation network, and the main groups active in patent registration were identified by the community detection technique. The patents were then divided into six technology categories: Safety and Security, Information Services, Public Safety and Environment Monitoring, Collaborative Aware Systems, Smart Homes/Buildings, and Smart Grid. And their technical maturity was identified and examined using the Sigma Plot program. Based on the findings, information services technologies are in the saturation stage, while both smart homes/buildings, and smart grid technologies are in the saturation stage. Three technologies, Safety and Security, Public Safety and Environment Monitoring, and Collaborative Aware Systems are in the maturity stage

Comparison of different machine learning techniques on location extraction by utilizing geo-tagged tweets: A case study

In emergencies, Twitter is an important platform to get situational awareness simultaneously. Therefore, information about Twitter users’ location is a fundamental aspect to understand the disaster effects. But location extraction is a challenging task. Most of the Twitter users do not share their locations in their tweets. In that respect, there are different methods proposed for location extraction which cover different fields such as statistics, machine learning, etc. This study is a sample study that utilizes geo-tagged tweets to demonstrate the importance of the location in disaster management by taking three cases into consideration. In our study, tweets are obtained by utilizing the “earthquake” keyword to determine the location of Twitter users. Tweets are evaluated by utilizing the Latent Dirichlet Allocation (LDA) topic model and sentiment analysis through machine learning classification algorithms including the Multinomial and Gaussian Naïve Bayes, Support Vector Machine (SVM), Decision Tree, Random Forest, Extra Trees, Neural Network, k Nearest Neighbor (kNN), Stochastic Gradient Descent (SGD), and Adaptive Boosting (AdaBoost) classifications. Therefore, 10 different machine learning algorithms are applied in our study by utilizing sentiment analysis based on location-specific disaster-related tweets by aiming fast and correct response in a disaster situation. In addition, the effectiveness of each algorithm is evaluated in order to gather the right machine learning algorithm. Moreover, topic extraction via LDA is provided to comprehend the situation after a disaster. The gathered results from the application of three cases indicate that Multinomial Naïve Bayes and Extra Trees machine learning algorithms give the best results with an F-measure value over 80%. The study aims to provide a quick response to earthquakes by applying the aforementioned techniques. © 2020 Elsevier Lt

The evolution of interindustry technology linkage topics and its analysis framework in 3D printing technology

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordThe mutual influence and complementarity of technologies between different industries are becoming increasingly prominent. Revealing the topic evolution of technology linkages between industries is the foundation for understanding the technological development trend of the industry. Although numerous works have focused on technology topic mining and its evolution characteristics, these works have not accurately represented the interindustry technology linkage, analyze the related topics and even ignored the technological development characteristics hidden in the topic evolution pathway. Since the Lingo algorithm fully considers the time-series characteristics of the topics, and the knowledge evolution theory can reveal three inherent characteristics in the evolution of knowledge topics, namely, “stability, heredity, and variability,” this article aims to combine the Lingo algorithm and the knowledge evolution theory to analyze the topic evolution of interindustry technology linkages. Additionally, because three-dimensional (3-D) printing technology has significant interdisciplinary and cross-industry characteristics, a wide range of application fields, and various interindustry technology linkages, 3-D printing technology is used for empirical analysis. The empirical results show that the key topics of interindustry technology linkages in 3-D printing include model design, manufacturing methods, manufacturing equipment, manufacturing material, and application. In addition, all these topics have the development feature of heredity. However, the topic of manufacturing materials presents significant variability, the topic of manufacturing methods has the strongest stability, and multiple subtopics of the five topics show variability and genetic intersection

De animais a máquinas : humanos tecnicamente melhores nos imaginários de futuro da convergência tecnológica

Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Sociais, Departamento de Sociologia, 2020.O tema desta investigação é discutir os imaginários sociais de ciência e tecnologia que emergem a partir da área da neuroengenharia, em sua relação com a Convergência Tecnológica de quatro disciplinas: Nanotecnologia, Biotecnologia, tecnologias da Informação e tecnologias Cognitivas - neurociências- (CT-NBIC). Estas áreas desenvolvem-se e são articuladas por meio de discursos que ressaltam o aprimoramento das capacidades físicas e cognitivas dos seres humanos, com o intuito de construir uma sociedade melhor por meio do progresso científico e tecnológico, nos limites das agendas de pesquisa e desenvolvimento (P&D). Objetivos: Os objetivos nesse cenário, são discutir as implicações éticas, econômicas, políticas e sociais deste modelo de sistema sociotécnico. Nos referimos, tanto as aplicações tecnológicas, quanto as consequências das mesmas na formação dos imaginários sociais, que tipo de relações se estabelecem e como são criadas dentro desse contexto. Conclusão: Concluímos na busca por refletir criticamente sobre as propostas de aprimoramento humano mediado pela tecnologia, que surgem enquanto parte da agenda da Convergência Tecnológica NBIC. No entanto, as propostas de melhoramento humano vão muito além de uma agenda de investigação. Há todo um quadro de referências filosóficas e políticas que defendem o aprimoramento da espécie, vertentes estas que se aliam a movimentos trans-humanistas e pós- humanistas, posições que são ao mesmo tempo éticas, políticas e econômicas. A partir de nossa análise, entendemos que ciência, tecnologia e política estão articuladas, em coprodução, em relação às expectativas de futuros que são esperados ou desejados. Ainda assim, acreditamos que há um espaço de diálogo possível, a partir do qual buscamos abrir propostas para o debate público sobre questões de ciência e tecnologia relacionadas ao aprimoramento da espécie humana.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)The subject of this research is to discuss the social imaginaries of science and technology that emerge from the area of neuroengineering in relation with the Technological Convergence of four disciplines: Nanotechnology, Biotechnology, Information technologies and Cognitive technologies -neurosciences- (CT-NBIC). These areas are developed and articulated through discourses that emphasize the enhancement of human physical and cognitive capacities, the intuition it is to build a better society, through the scientific and technological progress, at the limits of the research and development (R&D) agendas. Objectives: The objective in this scenery, is to discuss the ethic, economic, politic and social implications of this model of sociotechnical system. We refer about the technological applications and the consequences of them in the formation of social imaginaries as well as the kind of social relations that are created and established in this context. Conclusion: We conclude looking for critical reflections about the proposals of human enhancement mediated by the technology. That appear as a part of the NBIC technologies agenda. Even so, the proposals of human enhancement go beyond boundaries that an investigation agenda. There is a frame of philosophical and political references that defend the enhancement of the human beings. These currents that ally to the transhumanism and posthumanism movements, positions that are ethic, politic and economic at the same time. From our analysis, we understand that science, technology and politics are articulated, are in co-production, regarding the expected and desired futures. Even so, we believe that there is a space of possible dialog, from which we look to open proposals for the public discussion on questions of science and technology related to enhancement of human beings