Context aware advertising

IP Television (IPTV) has created a new arena for digital advertising that has not been explored to its full potential yet. IPTV allows users to retrieve on demand content and recommended content; however, very limited research has been applied in the domain of advertising in IPTV systems. The diversity of the field led to a lot of mature efforts in the fields of content recommendation and mobile advertising. The introduction of IPTV and smart devices led to the ability to gather more context information that was not subject of study before. This research attempts at studying the different contextual parameters, how to enrich the advertising context to tailor better ads for users, devising a recommendation engine that utilizes the new context, building a prototype to prove the viability of the system and evaluating it on different quality of service and quality of experience measures. To tackle this problem, a review of the state of the art in the field of context-aware advertising as well as the related field of context-aware multimedia have been studied. The intent was to come up with the most relevant contextual parameters that can possibly yield a higher percentage precision for recommending advertisements to users. Subsequently, a prototype application was also developed to validate the feasibility and viability of the approach. The prototype gathers contextual information related to the number of viewers, their age, genders, viewing angles as well as their emotions. The gathered context is then dispatched to a web service which generates advertisement recommendations and sends them back to the user. A scheduler was also implemented to identify the most suitable time to push advertisements to users based on their attention span. To achieve our contributions, a corpus of 421 ads was gathered and processed for streaming. The advertisements were displayed in reality during the holy month of Ramadan, 2016. A data gathering application was developed where sample users were presented with 10 random ads and asked to rate and evaluate the advertisements according to a predetermined criteria. The gathered data was used for training the recommendation engine and computing the latent context-item preferences. This also served to identify the performance of a system that randomly sends advertisements to users. The resulting performance is used as a benchmark to compare our results against. When it comes to the recommendation engine itself, several implementation options were considered that pertain to the methodology to create a vector representation of an advertisement as well as the metric to use to measure the similarity between two advertisement vectors. The goal is to find a representation of advertisements that circumvents the cold start problem and the best similarity measure to use with the different vectorization techniques. A set of experiments have been designed and executed to identify the right vectorization methodology and similarity measure to apply in this problem domain. To evaluate the overall performance of the system, several experiments were designed and executed that cover different quality aspects of the system such as quality of service, quality of experience and quality of context. All three aspects have been measured and our results show that our recommendation engine exhibits a significant improvement over other mechanisms of pushing ads to users that are employed in currently existing systems. The other mechanisms placed in comparison are the random ad generation and targeted ad generation. Targeted ads mechanism relies on demographic information of the viewer with disregard to his/her historical consumption. Our system showed a precision percentage of 69.70% which means that roughly 7 out of 10 recommended ads are actually liked and viewed to the end by the viewer. The practice of randomly generating ads yields a result of 41.11% precision which means that only 4 out of 10 recommended ads are actually liked by viewers. The targeted ads system resulted in 51.39% precision. Our results show that a significant improvement can be introduced when employing context within a recommendation engine. When introducing emotion context, our results show a significant improvement in case the user’s emotion is happiness; however, it showed a degradation of performance when the user’s emotion is sadness. When considering all emotions, the overall results did not show a significant improvement. It is worth noting though that ads recommended based on detected emotions using our systems proved to always be relevant to the user\u27s current mood

Proceedings of the 2012 Workshop on Ambient Intelligence Infrastructures (WAmIi)

This is a technical report including the papers presented at the Workshop on Ambient Intelligence Infrastructures (WAmIi) that took place in conjunction with the International Joint Conference on Ambient Intelligence (AmI) in Pisa, Italy on November 13, 2012. The motivation for organizing the workshop was the wish to learn from past experience on Ambient Intelligence systems, and in particular, on the lessons learned on the system architecture of such systems. A significant number of European projects and other research have been performed, often with the goal of developing AmI technology to showcase AmI scenarios. We believe that for AmI to become further successfully accepted the system architecture is essential

Proceedings of the 2012 Workshop on Ambient Intelligence Infrastructures (WAmIi)

This is a technical report including the papers presented at the Workshop on Ambient Intelligence Infrastructures (WAmIi) that took place in conjunction with the International Joint Conference on Ambient Intelligence (AmI) in Pisa, Italy on November 13, 2012. The motivation for organizing the workshop was the wish to learn from past experience on Ambient Intelligence systems, and in particular, on the lessons learned on the system architecture of such systems. A significant number of European projects and other research have been performed, often with the goal of developing AmI technology to showcase AmI scenarios. We believe that for AmI to become further successfully accepted the system architecture is essential

Discovery and Push Notification Mechanisms for Mobile Cloud Services

Viimase viie aasta jooksul on mobiilsed seadmed nagu sülearvutid, pihuarvutid, nutitelefonid jmt. tunginud peaaegu kõigisse inimeste igapäevaelu tegevustesse. Samuti on põhjalik teadus- ja arendustegevus mobiilsete tehnoloogiate vallas viinud märkimisväärsete täiustusteni riistvara, tarkvara ja andmeedastuse alal. Tänapäeval on mobiilsed seadmed varustatud sisseehitatud sensorite, kaamera, puutetundliku ekraani, suurema hulga mäluga, kuid ka tõhusamate energiatarbemehhanismidega. Lisaks on iOS ja Android operatsioonisüsteemide väljalaske tõttu suurenenud nii mobiilirakenduste arv kui keerukus, pakkudes arvukamalt kõrgetasemelisi rakendusi. Sarnaselt on toimunud olulised arengud ja standardiseerimisele suunatud jõupingutused veebiteenusete valdkonnas ja elementaarsetele veebiteenuste ligipääsu kasutatakse laialdaselt nutitelefonidest. See on viinud loogilise järgmise sammuna veebiteenuste pakkumiseni nutitelefonidest. Telefonidest veebiteenuste pakkumise kontseptsioon ei ole uus ning seda on põhjalikult uurinud Srirama, kes pakkus välja Mobile Host (Mobiilne Veebiteenuse Pakkuja) kontseptsiooni. Algne realisatsioon kasutas aga aegunud tehnoloogiaid nagu JMEE, PersonalJava, SOAP arhitektuur jne. See töö uuendab Mobile Host'i kasutades uusimaid tehnoloogiad, nagu Android OS ja REST arhitektuur, ning pakub välja teenusemootori, mis põhineb Apache Felix'il - OSGi platvormi realisatsioonil piiratud ressurssidega seadmetele. Hämmastava kiirusega toimunud arengud mobiilsete arvutuste vallas võimaldavad uue põlvkonna veebirakenduste loomist valdkondades nagu keskkonnateadlikkus, sotsiaalvõrgustikud, koostöövahendid, asukohapõhised teenused jne. Sellised rakendused saavad ära kasutada Mobile Host'i võimalusi. Selle tulemusena on klientidel ligipääs väga suurele hulgale teenustele, mistõttu tekib vajadus efektiivse teenuste avastamise mehhanismi järele. See töö pakub välja kataloogipõhise avastusmehhanismi võrgu ülekatte toega suurtele, kõrge liikuvusega võrgustikele. See mehhanism toetub OWL-S'le, mis on ontoloogia veebiteenuseid pakkuvate ressursside avastamiseks, väljakutseks, koostamiseks ja jälgimiseks. Töö kirjeldab ka Srirama välja pakutud algupärast teenuste avastamise mehhanismi, mis toetub peer-to-peer võrkudele ja Apache Lucene võtmesõna otsingumootorile. Uurimuse käigus uuendatakse teenuseotsing kasutama Apache Solr'i, Apache Lucene'i viimast versiooni. Teenuste avastust testiti põhjalikult ja tulemused on töös kokkuvõtvalt välja toodud. Mobiilsete tehnoloogiate vallas uuritakse ka võimalust kasutada pilvetehnolologiat laiendamaks mobiilseadmete salvestusmahtu ja töökoormust edastades pilve andme- ja arvutusmahukad ülesanded. See soodustab keerulisemate ja võimalusrohkemate mobiilirakenduste arendust. Pilve delegeeritavate toimingute aeganõudva iseloomu tõttu aga on vajalik asünkroonne mehhanism teavitamaks kasutajat, millal töömahukad tegevused on lõpetatud. Mobiilsete pilveteenuste pakkujad ja vahevara lahendused võivad kasu saada Mobile Host'ist ja selle asünkroonsete teavituste võimekusest. Uurimus esitleb nelja teavitusmehhanismi: AC2DM, APNS, IBM MQTT ja Mobile Host'i põhine teavitus. Töö võtab kokku kvantitatiivse analüüsi tulemused ja toob välja nelja teavitamise lähenemise tugevused ja nõrkused. Lisaks kirjeldatakse CroudSTag rakenduse realisatsiooni - CroudSTag on mobiilirakendus, mille eesmärgiks on sotsiaalsete gruppide moodustamine kasutades näotuvastustehnoloogiat. CroudSTag-i realisatsioon kasutab mobiilseid pilveteenuseid ja Mobile Host'i, et pakkuda oma funktsionaalsust kasutajale.In the last lustrum the mobile devices such as laptops, PDAs, smart phones, tablets, etc. have pervaded almost all the environments where people perform their day-to-day activities. Further, the extensive Research and Development in mobile technologies has led to significant improvements in hardware, software and transmission. Similarly, there are significant developments and standardization efforts in web services domain and basic web services have been widely accessed from smart phones. This has lead to the logical next step of providing web services from the smart phones. The concept of the web service provisioning from smart phones is not new and has been extensively explored by Srirama who proposed the concept of Mobile Host. However, the original implementation considered aged technologies such as JMEE, PersonalJava, SOAP architecture among others. This work updates the Mobile Host to the latest technologies like Android OS and REST architecture and proposes a service engine based on Apache Felix, and OSGI implementation for resource constraint devices. Moreover, the astonishing speed in developments in mobile computing enable the new generation of applications from domains such as context-awareness, social network, collaborative tools, location based services, etc., which benefit from the Mobile Host service provisioning capabilities. As a result the clients have access to a huge number of services available; therefore, an efficient and effective service discovery mechanism is required. The thesis proposes a directory-based with network overlay support discovery mechanism for large networks with high mobility. The proposed discovery mechanism relies in OWL-S, an ontology for service discovery, invocation, composition, and monitoring of web resources. The work also considers the original service discovery mechanism proposed by Srirama relying in peer-to-peer networks and Apache Lucene, a keyword search engine. The study updates the service search to Apache Solr, the latest development for Apache Lucene. The service discovery was extensively tested and the results are summarized in this work. Mobile technologies are looking into the clouds for extending their capabilities in storage and processing by offloading data and process intensive tasks. This fosters the development of more complex and rich mobile applications. However, due to the time-consuming nature of the tasks delegated to the clouds, an asynchronous mechanism is necessary for notifying the user when the intensive tasks are completed. Mobile cloud service providers and Middleware solutions might benefit from Mobile Host and its asynchronous notification capabilities. The study presents four push notification mechanisms being AC2DM, APNS, IBM MQTT and Mobile Host based push notification. The work summarizes the results of a quantitative analysis and highlights the strengths and weakness of the four notifications approaches. In addition, it explains CroudSTag realization, a mobile application that aims the social group formation by means of facial recognition that relies in mobile cloud services and Mobile Host to provide its functionality to the user

Smart PIN: performance and cost-oriented context-aware personal information network

The next generation of networks will involve interconnection of heterogeneous individual networks such as WPAN, WLAN, WMAN and Cellular network, adopting the IP as common infrastructural protocol and providing virtually always-connected network. Furthermore, there are many devices which enable easy acquisition and storage of information as pictures, movies, emails, etc. Therefore, the information overload and divergent content’s characteristics make it difficult for users to handle their data in manual way. Consequently, there is a need for personalised automatic services which would enable data exchange across heterogeneous network and devices. To support these personalised services, user centric approaches for data delivery across the heterogeneous network are also required. In this context, this thesis proposes Smart PIN - a novel performance and cost-oriented context-aware Personal Information Network. Smart PIN's architecture is detailed including its network, service and management components. Within the service component, two novel schemes for efficient delivery of context and content data are proposed: Multimedia Data Replication Scheme (MDRS) and Quality-oriented Algorithm for Multiple-source Multimedia Delivery (QAMMD). MDRS supports efficient data accessibility among distributed devices using data replication which is based on a utility function and a minimum data set. QAMMD employs a buffer underflow avoidance scheme for streaming, which achieves high multimedia quality without content adaptation to network conditions. Simulation models for MDRS and QAMMD were built which are based on various heterogeneous network scenarios. Additionally a multiple-source streaming based on QAMMS was implemented as a prototype and tested in an emulated network environment. Comparative tests show that MDRS and QAMMD perform significantly better than other approaches