RESUMO
The retailing market has undergone a paradigm-shift in the last decades, departing from its traditional form of shopping in brick-and-mortar stores towards online shopping and the establishment of shopping malls. As a result, "small" independent retailers operating in urban environments have suffered a substantial reduction of their turnover. This situation could be presumably reversed if retailers were to establish business "alliances" targeting economies of scale and engage themselves in providing innovative digital services. The SMARTBUY ecosystem realizes the concept of a "distributed shopping mall", which allows retailers to join forces and unite in a large commercial coalition that generates added value for both retailers and customers. Along this line, the SMARTBUY ecosystem offers several novel features: (i) inventory management of centralized products and services, (ii) geo-located marketing of products and services, (iii) location-based search for products offered by neighboring retailers, and (iv) personalized recommendations for purchasing products derived by an innovative recommendation system. SMARTBUY materializes a blended retailing paradigm which combines the benefits of online shopping with the attractiveness of traditional shopping in brick-and-mortar stores. This article provides an overview of the main architectural components and functional aspects of the SMARTBUY ecosystem. Then, it reports the main findings derived from a 12 months-long pilot execution of SMARTBUY across four European cities and discusses the key technology acceptance factors when deploying alike business alliances.
RESUMO
Accurate motion estimation between frames is important for drastically reducing data redundancy in video coding. However, advanced motion estimation methods are computationally intensive and their execution in real time usually requires a parallel implementation. In this paper, we investigate the parallel implementation of such a motion estimation technique. Specifically, we present a parallel algorithm for motion estimation based on the bilinear transformation on the well-known parallel model of the hypercube network and formally prove the time and the space complexity of the proposed algorithm. We also show that the parallel algorithm can also run on other hypercubic networks, such as butterfly, cube-connected-cycles, shuffle-exchange or de Bruijn network with only constant slowdown.
RESUMO
Older adults' preferences to remain independent in their own homes along with the high costs of nursing home care have motivated the development of Ambient Assisted Living (AAL) technologies which aim at improving the safety, health conditions and wellness of the elderly. This paper reports hands-on experiences in designing, implementing and operating UbiCare, an AAL based prototype system for elderly home care monitoring. The monitoring is based on the recording of environmental parameters like temperature and light intensity as well as micro-level incidents which allows one to infer daily activities like moving, sitting, sleeping, usage of electrical appliances and plumbing components. The prototype is built upon inexpensive, off-the-shelf hardware (e.g., various sensors, Arduino microcontrollers, ZigBee-compatible wireless communication modules) and license-free software, thereby ensuring low system deployment costs. The network comprises nodes placed in a house's main rooms or mounted on furniture, one wearable node, one actuator node and a centralized processing element (coordinator). Upon detecting significant deviations from the ordinary activity patterns of individuals and/or sudden falls, the system issues automated alarms which may be forwarded to authorized caregivers via a variety of communication channels. Furthermore, measured environmental parameters and activity incidents may be monitored through standard web interfaces.
