Information provision improvement with a geofencing event-bases system

Nowadays there is a big percentage of the population, specially young users, which are smartphone users and there is a lot of information to be provided within the applications, information provision should be done carefully and should be accurate, otherwise an overload of information will be produced, and the user will discard the app which is providing the information. Mobile devices are becoming smarter and provide many ways to filter information. However, there are alternatives to improve information provision from the side of the application. Some examples are, taking into account the local time, considering the battery level before doing an action and checking the user location to send personalized information attached to that location. SmartCampus and SmartCities are becoming a reality and they have more and more data integrated every day. With all this amount of data it is crucial to decide when and where is the user going to receive a notification with new information. Geofencing is a technique which allows applications to deliver information in a more useful way, in the right time and in the right place. It consists of geofences, physical regions delimited by boundaries, and devices that are eligible to receive the information assigned to the geofence. When devices cross one of these geofences an alert is pushed to the mobile device with the information.

Creation of a web application for smart park system and parking prediction study for system integration

In the last few years, we have observed an exponential increasing of the information systems, and parking information is one more example of them. The needs of obtaining reliable and updated information of parking slots availability are very important in the goal of traffic reduction. Also parking slot prediction is a new topic that has already started to be applied. San Francisco in America and Santander in Spain are examples of such projects carried out to obtain this kind of information. The aim of this thesis is the study and evaluation of methodologies for parking slot prediction and the integration in a web application, where all kind of users will be able to know the current parking status and also future status according to parking model predictions. The source of the data is ancillary in this work but it needs to be understood anyway to understand the parking behaviour. Actually, there are many modelling techniques used for this purpose such as time series analysis, decision trees, neural networks and clustering. In this work, the author explains the best techniques at this work, analyzes the result and points out the advantages and disadvantages of each one. The model will learn the periodic and seasonal patterns of the parking status behaviour, and with this knowledge it can predict future status values given a date. The data used comes from the Smart Park Ontinyent and it is about parking occupancy status together with timestamps and it is stored in a database. After data acquisition, data analysis and pre-processing was needed for model implementations. The first test done was with the boosting ensemble classifier, employed over a set of decision trees, created with C5.0 algorithm from a set of training samples, to assign a prediction value to each object. In addition to the predictions, this work has got measurements error that indicates the reliability of the outcome predictions being correct. The second test was done using the function fitting seasonal exponential smoothing tbats model. Finally as the last test, it has been tried a model that is actually a combination of the previous two models, just to see the result of this combination. The results were quite good for all of them, having error averages of 6.2, 6.6 and 5.4 in vacancies predictions for the three models respectively. This means from a parking of 47 places a 10% average error in parking slot predictions. This result could be even better with longer data available. In order to make this kind of information visible and reachable from everyone having a device with internet connection, a web application was made for this purpose. Beside the data displaying, this application also offers different functions to improve the task of searching for parking. The new functions, apart from parking prediction, were: - Park distances from user location. It provides all the distances to user current location to the different parks in the city. - Geocoding. The service for matching a literal description or an address to a concrete location. - Geolocation. The service for positioning the user. - Parking list panel. This is not a service neither a function, is just a better visualization and better handling of the information.

Indoor location-based analytics systems: Portuguese market compettive assessment and entry procing strategy of BIPs' technology in Sonae Sierra Shopping malls stores

This project attempts to provide an in-depth competitive assessment of the Portuguese indoor location-based analytics market, and to elaborate an entry-pricing strategy for Business Intelligence Positioning System (BIPS) implementation in Portuguese shopping centre stores. The role of industry forces and company’s organizational resources platform to sustain company’s competitive advantage was explored. A customer value-based pricing approach was adopted to assess BIPS value to retailers and maximize Sonae Sierra profitability. The exploratory quantitative research found that there is a market opportunity to explore every store area types with tailored proposals, and to set higher-than-tested membership fees to allow a rapid ROI, concluding there are propitious conditions for Sierra to succeed in BIPS store’s business model in Portugal.

Therapeutics bioconjugates: evaluation of iminoboronates as payload delivery system for cancer

The advent of bioconjugation impacted deeply the world of sciences and technology. New biomolecules were found, biological processes were understood, and novel methodologies were formed due to the fast expansion of this area. The possibility of creating new effective therapies for diseases like cancer is one of big applications of this now big area of study. Off target toxicity was always the problem of potent small molecules with high activity towards specific tumour targets. However, chemotherapy is now selective due to powerful linkers that connect targeting molecules with affinity to interesting biological receptors and cytotoxic drugs. This linkers must have very specific properties, such as high stability in plasma, no toxicity, no interference with ligand affinity nor drug potency, and at the same time, be able to lyse once inside the target molecule to release the therapeutic warhead. Bipolar environments between tumour intracellular and extracellular medias are usually exploited by this linkers in order to complete this goal. The work done in this thesis explores a new model for that same task, specific cancer drug delivery. Iminoboronates were studied due to its remarkable selective stability towards a wide pH range and endogenous molecules. A fluorescence probe was design to validate this model by creating an Off/On system and determine the payload release location in situ. A process was optimized to synthetize the probe 8-(1-aminoethyl)-7-hydroxy-coumarin (1) through a reductive amination reaction in a microwave reactor with 61 % yield. A method to conjugate this probe to ABBA was also optimized, obtaining the iminoboronate in good yields in mild conditions. The iminoboronate model was studied regarding its stability in several simulated biological environments and each half-life time was determined, showing the conjugate is stable most of the cases except in tumour intracellular systems. The construction of folate-ABBA-coumarin bioconjugate have been made to complete this evaluation. The ability to be uptaken by a cancer cell through endocytosis process and the conjugation delivery of coumarin fluorescence payload are two features to hope for in this construct.