A service-oriented middleware for integrated management of crowdsourced and sensor data streams in disaster management

The increasing number of sensors used in diverse applications has provided a massive number of continuous, unbounded, rapid data and requires the management of distinct protocols, interfaces and intermittent connections. As traditional sensor networks are error-prone and difficult to maintain, the study highlights the emerging role of “citizens as sensors” as a complementary data source to increase public awareness. To this end, an interoperable, reusable middleware for managing spatial, temporal, and thematic data using Sensor Web Enablement initiative services and a processing engine was designed, implemented, and deployed. The study found that its approach provided effective sensor data-stream access, publication, and filtering in dynamic scenarios such as disaster management, as well as it enables batch and stream management integration. Also, an interoperability analytics testing of a flood citizen observatory highlighted even variable data such as those provided by the crowd can be integrated with sensor data stream. Our approach, thus, offers a mean to improve near-real-time applications

Self-localisation in indoor environments combining learning and evolution with wireless networks

This work combines wireless networks (WLAN) (Wireless\ud LAN IEEE 802.11 b/g) with learning and evolution of arti\ud cial neural networks. Our main objective is to propose\ud an architecture for a self-adaptive system, addressing alternative\ud methods to the usage of GPS for self-localisation in\ud autonomous mobile robots either in indoor or outdoor environments.\ud We seek to describe alternatives and evaluation\ud methods for localisation of mobile agents using the strength\ud signal from Access Points (APs). The results show that the\ud proposed method used with autonomous mobile robots does\ud not require the use of special hardware, and hence is low\ud cost, easy to operate, and fully autonomousCNPq - INCT-SEC (processo No. 573963/2008-8 e 08/57870-9)FAPESP (processo No. 2012/22550-0)CAPES (processo No. BEX 4202-11-2