The crowd as a cameraman : on-stage display of crowdsourced mobile video at large-scale events

Recording videos with smartphones at large-scale events such as concerts and festivals is very common nowadays. These videos register the atmosphere of the event as it is experienced by the crowd and offer a perspective that is hard to capture by the professional cameras installed throughout the venue. In this article, we present a framework to collect videos from smartphones in the public and blend these into a mosaic that can be readily mixed with professional camera footage and shown on displays during the event. The video upload is prioritized by matching requests of the event director with video metadata, while taking into account the available wireless network capacity. The proposed framework's main novelty is its scalability, supporting the real-time transmission, processing and display of videos recorded by hundreds of simultaneous users in ultra-dense Wi-Fi environments, as well as its proven integration in commercial production environments. The framework has been extensively validated in a controlled lab setting with up to 1 000 clients as well as in a field trial where 1 183 videos were collected from 135 participants recruited from an audience of 8 050 people. 90 % of those videos were uploaded within 6.8 minutes

Self-Liquidating Sales Funnel For a Cloud Manufacturer

The objective of this project was to develop a self-liquidating sales funnel for a cloud manufacturing company. The rationale included the cost effectiveness to generate leads. Market research was performed, a funnel was developed and a pro-forma financial analysis was completed. The results of the project produced marketing personas, a funnel design and a NPV analysis for advertising spending. It was concluded that a self-liquidating sales funnel is viable for the sponsor

LOCATION-BASED MARKETING: CONCEPTS, TECHNOLOGIES AND SERVICES

siirretty Doriast

Streaming Big Data Analysis for Real-Time Sentiment based Targeted Advertising

Big Data constituting from the information shared in the various social network sites have great relevance for research to be applied in diverse fields like marketing, politics, health or disaster management. Social network sites like Facebook and Twitter are now extensively used for conducting business, marketing products and services and collecting opinions and feedbacks regarding the same. Since data gathered from these sites regarding a product/brand are up-to-date and are mostly supplied voluntarily, it tends to be more realistic, massive and reflects the general public opinion. Its analysis on real time can lead to accurate insights and responding to the results sooner is undoubtedly advantageous than responding later.  In this paper, a cloud based system for real time targeted advertising based on tweet sentiment analysis is designed and implemented using the big data processing engine Apache Spark, utilizing its streaming library. Application is meant to promote cross selling and provide better customer support