Multi-contrast imaging and digital refocusing on a mobile microscope with a domed LED array

We demonstrate the design and application of an add-on device for improving the diagnostic and research capabilities of CellScope--a low-cost, smartphone-based point-of-care microscope. We replace the single LED illumination of the original CellScope with a programmable domed LED array. By leveraging recent advances in computational illumination, this new device enables simultaneous multi-contrast imaging with brightfield, darkfield, and phase imaging modes. Further, we scan through illumination angles to capture lightfield datasets, which can be used to recover 3D intensity and phase images without any hardware changes. This digital refocusing procedure can be used for either 3D imaging or software-only focus correction, reducing the need for precise mechanical focusing during field experiments. All acquisition and processing is performed on the mobile phone and controlled through a smartphone application, making the computational microscope compact and portable. Using multiple samples and different objective magnifications, we demonstrate that the performance of our device is comparable to that of a commercial microscope. This unique device platform extends the field imaging capabilities of CellScope, opening up new clinical and research possibilities

Detection of Road Conditions Using Image Processing and Machine Learning Techniques for Situation Awareness

In this modern era, land transports are increasing dramatically. Moreover, self-driven car or the Advanced Driving Assistance System (ADAS) is now the public demand. For these types of cars, road conditions detection is mandatory. On the other hand, compared to the number of vehicles, to increase the number of roads is not possible. Software is the only alternative solution. Road Conditions Detection system will help to solve the issues. For solving this problem, Image processing, and machine learning have been applied to develop a project namely, Detection of Road Conditions Using Image Processing and Machine Learning Techniques for Situation Awareness. Many issues could be considered for road conditions but the main focus will be on the detection of potholes, Maintenance sings and lane. Image processing and machine learning have been combined for our system for detecting in real-time. Machine learning has been applied to maintains signs detection. Image processing has been applied for detecting lanes and potholes. The detection system will provide a lane mark with colored lines, the pothole will be a marker with a red rectangular box and for a road Maintenance sign, the system will also provide information of aintenance sign as maintenance sing is detected. By observing all these scenarios, the driver will realize the road condition. On the other hand situation awareness is the ability to perceive information from it’s surrounding, takes decisions based on perceived information and it makes decision based on prediction

Intel Galileo and Intel Galileo Gen 2

Computer scienc

Do-it-yourself instruments and data processing methods for developing marine citizen observatories

La consulta íntegra de la tesi, inclosos els articles no comunicats públicament per drets d'autor, es pot realitzar prèvia petició a l'Arxiu de la UPCWater is the most important resource for living on planet Earth, covering more than 70% of its surface. The oceans represent more than 97% of the planet total water and they are where more than the 99.5% of the living beings are concentrated. A great number of ecosystems depend on the health of these oceans; their study and protection are necessary. Large datasets over long periods of time and over wide geographical areas can be required to assess the health of aquatic ecosystems. The funding needed for data collection is considerable and limited, so it is important to look at new cost-effective ways of obtaining and processing marine environmental data. The feasible solution at present is to develop observational infrastructures that may increase significantly the conventional sampling capabilities. In this study we promote to achieve this solution with the implementation of Citizen Observatories, based on volunteer participation. Citizen observatories are platforms that integrate the latest information technologies to digitally connect citizens, improving observation skills for developing a new type of research known as Citizen Science. Citizen science has the potential to increase the knowledge of the environment, and aquatic ecosystems in particular, through the use of people with no specific scientific training to collect and analyze large data sets. We believe that citizen science based tools -open source software coupled with low-cost do-it-yourself hardware- can help to close the gap between science and citizens in the oceanographic field. As the public is actively engaged in the analysis of data, the research also provides a strong avenue for public education. This is the objective of this thesis, to demonstrate how open source software and low-cost do-it-yourself hardware are effectively applied to oceanographic research and how can it develop into citizen science. We analyze four different scenarios where this idea is demonstrated: an example of using open source software for video analysis where lobsters were monitored; a demonstration of using similar video processing techniques on in-situ low-cost do-it-yourself hardware for submarine fauna monitoring; a study using open source machine learning software as a method to improve biological observations; and last but not least, some preliminar results, as proof of concept, of how manual water sampling could be replaced by low-cost do-it-yourself hardware with optical sensors.L’aigua és el recurs més important per la vida al planeta Terra, cobrint més del 70% de la seva superfície. Els oceans representen més del 70% de tota l'aigua del planeta, i és on estan concentrats més del 99.5% dels éssers vius. Un gran nombre d'ecosistemes depenen de la salut d'aquests oceans; el seu estudi i protecció són necessaris. Grans conjunts de dades durant llargs períodes de temps i al llarg d’amples àrees geogràfiques poden ser necessaris per avaluar la salut dels ecosistemes aquàtics. El finançament necessari per aquesta recol·lecció de dades és considerable però limitat, i per tant és important trobar noves formes més rendibles d’obtenir i processar dades mediambientals marines. La solució factible actualment és la de desenvolupar infraestructures observacionals que puguin incrementar significativament les capacitats de mostreig convencionals. En aquest estudi promovem que es pot assolir aquesta solució amb la implementació d’Observatoris Ciutadans, basats en la participació de voluntaris. Els observatoris ciutadans són plataformes que integren les últimes tecnologies de la informació amb ciutadans digitalment connectats, millorant les capacitats d’observació, per desenvolupar un nou tipus de recerca coneguda com a Ciència Ciutadana. La ciència ciutadana té el potencial d’incrementar el coneixement del medi ambient, i dels ecosistemes aquàtics en particular, mitjançant l'ús de persones sense coneixement científic específic per recollir i analitzar grans conjunts de dades. Creiem que les eines basades en ciència ciutadana -programari lliure juntament amb maquinari de baix cost i del tipus "fes-ho tu mateix" (do-it-yourself en anglès)- poden ajudar a apropar la ciència del camp oceanogràfic als ciutadans. A mesura que el gran públic participa activament en l'anàlisi de dades, la recerca esdevé també una nova via d’educació pública. Aquest és l’objectiu d’aquesta tesis, demostrar com el programari lliure i el maquinari de baix cost "fes-ho tu mateix" s’apliquen de forma efectiva a la recerca oceanogràfica i com pot desenvolupar-se cap a ciència ciutadana. Analitzem quatre escenaris diferents on es demostra aquesta idea: un exemple d’ús de programari lliure per anàlisi de vídeos de monitoratge de llagostes; una demostració utilitzant tècniques similars de processat de vídeo en un dispositiu in-situ de baix cost "fes-ho tu mateix" per monitoratge de fauna submarina; un estudi utilitzant programari lliure d’aprenentatge automàtic (machine learning en anglès) com a mètode per millorar observacions biològiques; i finalment uns resultats preliminars, com a prova de la seva viabilitat, de com un mostreig manual de mostres d’aigua podria ser reemplaçat per maquinari de baix cost "fes-ho tu mateix" amb sensors òptics.Postprint (published version

Moving patterns recognition & location for robotics

Romero Bretó, C. (2011). Moving patterns recognition & location for robotics. http://hdl.handle.net/10251/11388.Archivo delegad

Simulation and Planning of a 3D Spray Painting Robotic System

Nesta dissertação é proposto um sistema robótico 3D de pintura com spray. Este sistema inclui uma simulação realista do spray com precisão suficiente para imitar pintura com spray real. Também inclui um algoritmo otimizado para geração de caminhos que é capaz de pintar projetos 3D não triviais. A simulação parte de CAD 3D ou peças digitalizadas em 3D e produz um efeito visual realista que permite analisar qualitativamente o produto pintado. Também é apresentada uma métrica de avaliação que pontua trajetória de pintura baseada na espessura, uniformidade, tempo e desperdício de tinta.In this dissertation a 3D spray painting robotic system is proposed. This system has realistic spray simulation with sufficient accuracy to mimic real spray painting. It also includes an optimized algorithm for path generation that is capable of painting non trivial 3D designs. The simulation has 3D CAD or 3D scanned input pieces and produces a realistic visual effect that allows qualitative analyses of the painted product. It is also presented an evaluation metric that scores the painting trajectory based on thickness, uniformity, time and waste of paint

Do-it-yourself instruments and data processing methods for developing marine citizen observatories

Water is the most important resource for living on planet Earth, covering more than 70% of its surface. The oceans represent more than 97% of the planet total water and they are where more than the 99.5% of the living beings are concentrated. A great number of ecosystems depend on the health of these oceans; their study and protection are necessary. Large datasets over long periods of time and over wide geographical areas can be required to assess the health of aquatic ecosystems. The funding needed for data collection is considerable and limited, so it is important to look at new cost-effective ways of obtaining and processing marine environmental data. The feasible solution at present is to develop observational infrastructures that may increase significantly the conventional sampling capabilities. In this study we promote to achieve this solution with the implementation of Citizen Observatories, based on volunteer participation. Citizen observatories are platforms that integrate the latest information technologies to digitally connect citizens, improving observation skills for developing a new type of research known as Citizen Science. Citizen science has the potential to increase the knowledge of the environment, and aquatic ecosystems in particular, through the use of people with no specific scientific training to collect and analyze large data sets. We believe that citizen science based tools -open source software coupled with low-cost do-it-yourself hardware- can help to close the gap between science and citizens in the oceanographic field. As the public is actively engaged in the analysis of data, the research also provides a strong avenue for public education. This is the objective of this thesis, to demonstrate how open source software and low-cost do-it-yourself hardware are effectively applied to oceanographic research and how can it develop into citizen science. We analyze four different scenarios where this idea is demonstrated: an example of using open source software for video analysis where lobsters were monitored; a demonstration of using similar video processing techniques on in-situ low-cost do-it-yourself hardware for submarine fauna monitoring; a study using open source machine learning software as a method to improve biological observations; and last but not least, some preliminar results, as proof of concept, of how manual water sampling could be replaced by low-cost do-it-yourself hardware with optical sensors.L’aigua és el recurs més important per la vida al planeta Terra, cobrint més del 70% de la seva superfície. Els oceans representen més del 70% de tota l'aigua del planeta, i és on estan concentrats més del 99.5% dels éssers vius. Un gran nombre d'ecosistemes depenen de la salut d'aquests oceans; el seu estudi i protecció són necessaris. Grans conjunts de dades durant llargs períodes de temps i al llarg d’amples àrees geogràfiques poden ser necessaris per avaluar la salut dels ecosistemes aquàtics. El finançament necessari per aquesta recol·lecció de dades és considerable però limitat, i per tant és important trobar noves formes més rendibles d’obtenir i processar dades mediambientals marines. La solució factible actualment és la de desenvolupar infraestructures observacionals que puguin incrementar significativament les capacitats de mostreig convencionals. En aquest estudi promovem que es pot assolir aquesta solució amb la implementació d’Observatoris Ciutadans, basats en la participació de voluntaris. Els observatoris ciutadans són plataformes que integren les últimes tecnologies de la informació amb ciutadans digitalment connectats, millorant les capacitats d’observació, per desenvolupar un nou tipus de recerca coneguda com a Ciència Ciutadana. La ciència ciutadana té el potencial d’incrementar el coneixement del medi ambient, i dels ecosistemes aquàtics en particular, mitjançant l'ús de persones sense coneixement científic específic per recollir i analitzar grans conjunts de dades. Creiem que les eines basades en ciència ciutadana -programari lliure juntament amb maquinari de baix cost i del tipus "fes-ho tu mateix" (do-it-yourself en anglès)- poden ajudar a apropar la ciència del camp oceanogràfic als ciutadans. A mesura que el gran públic participa activament en l'anàlisi de dades, la recerca esdevé també una nova via d’educació pública. Aquest és l’objectiu d’aquesta tesis, demostrar com el programari lliure i el maquinari de baix cost "fes-ho tu mateix" s’apliquen de forma efectiva a la recerca oceanogràfica i com pot desenvolupar-se cap a ciència ciutadana. Analitzem quatre escenaris diferents on es demostra aquesta idea: un exemple d’ús de programari lliure per anàlisi de vídeos de monitoratge de llagostes; una demostració utilitzant tècniques similars de processat de vídeo en un dispositiu in-situ de baix cost "fes-ho tu mateix" per monitoratge de fauna submarina; un estudi utilitzant programari lliure d’aprenentatge automàtic (machine learning en anglès) com a mètode per millorar observacions biològiques; i finalment uns resultats preliminars, com a prova de la seva viabilitat, de com un mostreig manual de mostres d’aigua podria ser reemplaçat per maquinari de baix cost "fes-ho tu mateix" amb sensors òptics

3D scanning and detection of objects for a subsequent manipulation by a collaborative robot

Proyecto de Graduación (Licenciatura en Ingeniería en Mecatrónica) Instituto Tecnológico de Costa Rica, Área Académica de Ingeniería en Mecatrónica, 2016.The present document is a brief description of what the project "3D scanning and detection of objects for a subsequent manipulation by a collaborative robot" will be about, and how the solution will be approached. The project is developed as a final requirement to obtain the degree of "Licenciatura" in Mechatronic Engineering at the Tecnológico de Costa Rica. On the first part, the context of the project will be presented. It will be introduced different applications for 3D mapping technologies that can be found nowadays, as well as the different algorithms that are commonly used in this type of applications. It will be presented an outlook of some of the obstacles that might occur when handling this type of technology, and also the main authors and documents that were used to build a prospect of the realization of the project. On the consequent part, it will be defined the problem to be resolved, with the environment where it will be developed. Also, the main problem will be divided in several steps, to facilitate the achievement of the overall project. Finally, it will be presented the motivation for the interested part to develop a project of such nature. The next section will describe a strategy proposed to approach a solution for the entire project. It will be explained in more detail what each stage of the solution consist, and how every one of them is intended to be resolved. Ishikawa diagrams will be used as a tool to identify different problems present on the work, and the possible root causes that may be inducing each problem. After this, the Objectives section will present both the general and specific objectives for this project, together with a specific indicator for each objective. In the "Project execution" section, it will be detailed a list of steps to realize, to achieve the goals of the project. After this, a Gantt Diagram will be presented as an approximate to distribute time efficiently for the project. After this, a small summary of the expenses of the project will be presented, to understand the impact and feasibility of the project. 10 On the Solution's detailed description section, it will be described with detail all the steps that were taken to develop the project and to achieve the desired objectives. This section will be sub-divided to present the solution for each phase independently, with a final integration phase that connects all the solutions developed. After presenting the solutions developed, an analysis section will be described, where the strengths and weaknesses of the project will be described. Followed by this section, the conclusions of the project will be stated and after this, it will be presented a section that mentions different recommendations and future work that can be developed after this project, to give continuity and achieve more goals on the future. Finally, it will be presented a list of the sources and authors used to develop this document, as well as the important documents in the corresponding Appendix section.Duale Hochschule Baden Wuertemberg (DHBW) Universit