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About us
The IMPReSS project is a 30-months EU-Brazil cooperative research project started in 2013.

The project is partly funded by the European Commission under the 7th Framework Programme in the area of EU-Brazil Research and Development cooperation under Grant Agreement no. 614100

The Brazilian funding is provided by CNPq Conselho Nacional de Desenvolvimento Científico e Tecnológico

 

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Download title Date Author Version Downloads Comments Rating
Public Deliverables
Public deliverables are available for download once they have been officially accepted by the EC.
D5.1.1 Initial Data Analysis & Knowledge Repository Technical Specifications & Guidelines 26.03.15 1.0 536 0 --
This deliverable describes the initial technical specification of the data and knowledge repository used by the IMPReSS cloud. In the IMPReSS cloud, data semantics and analytics are fundamental to the the decision making process.
D8.3.1 Application Development_The_Teatro_Amazonas_Initial_Prototype 26.03.15 1.0 566 0 --
This deliverable describes how the structure of Amazonas Theater will be used to install sensors, which measures must be obtained, and how to build a demo to show the system to the public.
D8.1 Specification of Proof-of-Concept Applications 26.03.15 1.1 609 0 --
This deliverable describes the initial proposal for the specification of the proof-of-concept applications leveraging on the Impress cloud for the Teatro Amazonas and the UFPE campus.
D5.2 Data Analysis and Forecast for Energy Consumption 26.03.15 1.0 554 0 --
This deliverable focuses on showing how developers can use the IMPReSS platform to get insight from the massive amount of data acquired from smart objects connected to the IMPReSS Cloud.
D2.1.2 Requirement and Lessons Learned Report 21.05.16 1.0 419 0 --
This deliverable is follow-up of the deliverable D2.1.1 Initial Requirement Report. The deliverable presents the results of the Lessons Learned process as carried out in this first cycle of the project and an updated and current list of System Development
D3.2 Resource and Service Discovery Solutions 21.05.16 1.0 427 0 --
This deliverable defines the basis for discover and use of resources and services in the IMPReSS project. It is based on the current development plan and architecture.
D3.3 Communication Management 21.05.16 1.0 409 0 --
This deliverable describes the IMPReSS communication management, which is extended from the LinkSmart middleware. In this deliverable, we describe an overhaul of the communication management concept involving local network communication (communication whi
D3.4 Network Management 21.05.16 1.0 409 0 --
This deliverable describes a novel network management infrastructure for the Internet of Things, which has been developed in the T3.4 - Network Management.
D4.1.2 Final application classification language and tool 21.05.16 1.0 2917 0 --
This deliverable focuses on the development part of the resource management framework. In the D4.1.1, we presented the possible meta-information that can be used by the GRM to assign the resources to an application. In this deliverable, we present the fur
D4.3 Resource Management & Access Scheduler 21.05.16 1.0 387 0 --
This deliverable describes the overall approach, architecture and reference implementation of the mixed criticality resource management component of the IMPReSS platform. This is a Prototype deliverable and the source code with examples can be downloaded
D4.4 Security of resource-constrained subsystems 21.05.16 1.0 397 0 --
This deliverable describes the work done in task 4.4 Security of resource-constrained subsystems. Deliverable specifies how security of IMPReSS resource-constrained subsystems is handled.
D5.1.2 Updated Data Analysis & Knowledge Repository Technical Specifications & Guidelines 21.05.16 1.0 375 0 --
This deliverable describes the updated technical specification of the data and knowledge
repository used by the IMPReSS cloud. In the IMPReSS cloud, data semantics and analytics are
fundamental to the the decision making process. Effectively managing th
D5.3 Data Mining and Machine Learning Tools 21.05.16 1.0 417 0 --
This deliverable describes a web application used to provide machine learning techniques to help developers to identify environmental tendencies. The purpose of this web application is to help developers that do not have any knowledge in machine learning
D5.4 Machine Learning for User Behaviour and Occupancy Analysis 21.05.16 1.0 399 0 --
This deliverable describes scenarios to analyze user behaviour and occupancy using machine learning algorithms. Some practical scenarios that can be applied for diminishing electricity in a certain environment are proposed. All the steps to create these s
D6.4 Implementation of Context Reasoning Engine 21.05.16 1.0 737 0 --
This deliverable is aimed at providing a clear understanding the Context Manager focusing on implementation details and choices.
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