Power transfer through strongly coupled resonances

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Physics, 2007.Includes bibliographical references (leaves 41-42).Using self-resonant coils in a strongly coupled regime, we experimentally demonstrate efficient non-radiative power transfer over distances of up to eight times the radius of the coils. We use this system to transfer 60W with approximately 45% efficiency over distances in excess of two meters. We present a quantitative model describing the power transfer which matches the experimental results to within 5%, and perform a finite element analysis of the objects used. We finally discuss the robustness of the mechanism proposed and consider safety and interference concerns.by André Kurs.S.M

Load monitoring and output power control of a wireless power transfer system without any wireless communication feedback

For mid-range wireless power applications, the load is normally far away from the power source. In this project, a new method is proposed to determine the load impedance and load power without using any direct output feedback. Based only on the information of the input voltage and current, the load impedance and load power can be monitored and controlled without using any wired or wireless feedback from the load. This new method can therefore eliminate the need for any directly measured output feedback, which was previously thought to be essential. It also makes the power control of a wireless power transfer very simple. The concept is verified by the comparison between the computed results and practical results of an 8-ring domino wireless power transfer system. A good degree of accuracy has been achieved in the verification. 2013 IEEE.published_or_final_versio

Performance Analysis of Blockchain-Enabled Security and Privacy Algorithms in Connected and Autonomous Vehicles: A Comprehensive Review

Strategic investment(s) in vehicle automation technologies led to the rapid development of technology that revolutionised transport services and reduced fatalities on a scale never seen before. Technological advancements and their integration in Connected Autonomous Vehicles (CAVs) increased uptake and adoption and pushed firmly for the development of highly supportive legal and regulatory and testing environments. However, systemic threats to the security and privacy of technologies and lack of data transparency have created a dynamic threat landscape within which the establishment and verification of security and privacy requirements proved to be an arduous task. In CAVs security and privacy issues can affect the resilience of these systems and hinder the safety of the passengers. Existing research efforts have been placed to investigate the security issues in CAVs and propose solutions across the whole spectrum of cyber resilience. This paper examines the state-of-the-art in security and privacy solutions for CAVs. It investigates their integration challenges, drawbacks and efficiencies when coupled with distributed technologies such as Blockchain. It has also listed different cyber-attacks being investigated while designing security and privacy mechanism for CAVs

Automates: the future of autonomous cars

El futur dels cotxes autònoms sembla brillant, tot i així, personatges com el mateix Elon Musk, entre d'altres, ens porten prometent que serien part de les nostres vides des de fa gairebé deu anys. Tot i això aquí seguim, amb els nostres vehicles que sí, que són genials, però de moment encara no es condueixen sols. Aquestes falses promeses i el concepte de que una màquina condueixi el cotxe per nosaltres encara genera rebuig a la majoria de la població, quan de fet més d'un 90% dels accidents de trànsit avui dia són a causa de l'error humà, i aquestes màquines seran moltes coses, però precisament humanes de moment no són. En aquest projecte s’indaga sobre l’estat actual d’aquests vehicles, que de fet certs serveis de cotxes autònoms ja ronden els carrers d’algunes de les ciutats més grans del món, com ara San Francisco. La clau és descobrir si els vehicles autònoms tenen el potencial real de convertir-se en el servei del futur. Per això, es recorre a les metodologies de Disseny de Futurs, analitzant les tendències del sector i així presentant una sèrie d'Escenaris Futurs. Aquestes metodologies ens permetran entreveure cap on ens porten els desenvolupaments actuals, per així descobrir els passos que hauríem de seguir i els que no per a una correcta i eficient implementació d'aquestes tecnologies en un futur més aviat proper que llunyà.El futuro de los coches autónomos parece brillante, aún así, personajes como el mismísimo Elon Musk, entre otros, nos llevan prometiendo que iban a ser parte de nuestras vidas desde hace ya casi diez años. Sin embargo aquí seguimos, con nuestros vehículos que sí, que son geniales, pero de momento aún no se conducen solos. Estas falsas promesas y el concepto de que una máquina conduzca el coche por nosotros aún genera rechazo en la mayoría de la población, cuando lo cierto es que más de un 90% de los accidentes de tráfico hoy en día son a causa del error humano, y estas máquinas serán muchas cosas pero precisamente humanas no son. En este proyecto se indaga sobre el estado actual de estos vehículos, que de hecho ciertos servicios de coches autónomos ya rondan las calles de algunas de las ciudades más grandes del mundo, como por ejemplo San Francisco. La clave es descubrir si los vehículos autónomos tienen el potencial real de convertirse en el servicio del futuro. Para ello, se recurre a las metodologías de Diseño de Futuros, analizando las tendencias del sector y así presentando una serie de Escenarios Futuros. Estas metodologías nos permitirán vislumbrar hacia dónde nos llevan los desarrollos actuales, para así descubrir los pasos que deberíamos seguir y los que no para una correcta y eficiente implementación de estas tecnologías en un futuro más próximo que lejano.The future of autonomous cars seems bright, even though, famous people like Elon Musk himself, among others, have been making promises around the fact that those cars would be part of our lives for almost ten years, but here we are, with our vehicles that are great, but for now they still don't drive for themselves. These false promises and the concept of a machine driving a car for us still generates rejection in the majority of the population, when the fact is that more than 90% of traffic accidents nowadays are due to human error, and these machines will be sort of things but not humans at all. This project investigates the current state of these vehicles, that in fact these autonomous car services already transit the streets of some of the largest cities in the world, cities like San Francisco. The key is to find out if autonomous vehicles have the real potential to become the service of the future. Therefore, Futures Design methodologies are used, analysing the trends of the sector and thus presenting a series of Future Scenarios. These methodologies will allow us to understand where current developments are leading us, so then we can understand the steps that we should follow as a society and those that we should not for a correct and efficient implementation of these technologies in the near future

Artificial Intelligence in Modern Society

Artificial intelligence is progressing rapidly into diverse areas in modern society. AI can be used in several areas such as research in the medical field or creating innovative technology, for instance, autonomous vehicles. Artificial intelligence is used in the medical field to improve the accuracy of programs used for detecting health conditions. AI technology is also used in programs such as Netflix or Spotify. This type of AI will monitor a user’s habits and make recommendations based on their recent activity. Banks use AI systems to monitor activity on members’ accounts to check for identity theft, approve loans and maintain online security. Systems like these can even be found in call centers. These programs analyze a caller’s voice in real time to provide information to the call center which helps them build a faster rapport with the caller. The purpose of this research paper is to explain how artificial intelligence is creating advanced technologies in various fields of study which will create a more efficient society

Adaptive routing of autonomous vehicles using neighborhood traffic

As research on autonomous vehicles increases, automotive manufacturers and researchers are developing coordination techniques to enable safe passage of vehicles through intersections. These techniques are called Autonomous Intersection Management (AIM). Even though AIM techniques improve intersection throughput, they do not effectively reduce congestion. Real life urban roads comprise of a networks of multiple intersections. In such scenarios, communicating traffic information between intersections is essential for reducing congestion on the roads. To achieve this, we propose an adaptive routing algorithm that incorporates a fusion of vehicle-to-intersection (V2I) communication and intersection-to-intersection (I2I) communication in order to bring about significant reductions in congestion. To implement this algorithm, we constructed the Enhanced AIM simulation framework as an extension of AIM simulator (University of Texas, Austin). We demonstrate with simulation experiments that our proposed routing algorithm shows reduced congestion and wait-time, and improved user experience.autonomous vehiclesAutonomous Intersection Management (AIM)urban roadsneighborhood traffi

The diffusion of disruptive technologies

We identify novel technologies using textual analysis of patents, job postings, and earnings calls. Our approach enables us to identify and document the diffusion of 29 disruptive technologies across firms and labor markets in the U.S. Five stylized facts emerge from our data. First, the locations where technologies are developed that later disrupt businesses are geographically highly concentrated, even more so than overall patenting. Second, as the technologies mature and the number of new jobs related to them grows, they gradually spread across space. While initial hiring is concentrated in high-skilled jobs, over time the mean skill level in new positions associated with the technologies declines, broadening the types of jobs that adopt a given technology. At the same time, the geographic diffusion of low-skilled positions is significantly faster than higher-skilled ones, so that the locations where initial discoveries were made retain their leading positions among high-paying positions for decades. Finally, these technology hubs are more likely to arise in areas with universities and high skilled labor pools

AI meets Digital: A Critical Review on Artificial Intelligence in Digital Entrepreneurship

Driven by a reduction in the cost of data generation and computing power and simultaneous advancement of mathematical methods, algorithms are becoming increasingly capable of mimicking human learning, profound judgment, and decision-making, even outperforming humans in doing so. This recent emergence of artificial intelligence (AI) seems to not only change the way how entrepreneurial endeavors operate but also the way how they emerge. In general, digital technologies are prone to render the processes and outcomes behind entrepreneurial endeavors less bounded and the locus of an entrepreneurial agency less predefined. Addressing the role of AI in this is only nascent so far. We thus suggest it is time to perform a critical review of the literature at the intersection of AI and digital entrepreneurship. Our investigation adopts a socio-technical lens to capture the state of the AI entrepreneurship literature and identify promising research avenues to trigger further discussions