DynaCargo

Intelligent transportation systems are a key component for ecologically sustainable development. The DynaCargo  project aims at developing a cargo-centric transport management system. DynaCargo extends and expands existing fleet management system functionality in two directions. The first direction is to fuse data collection, analyze and monitor related information ahead the time of cargo moment. This innovative approach, along with data analytics and routing optimization algorithms, will allow dynamic and automated adaptation of the fleet routing and cargo delivery plan across the whole hauling cycle. The second direction is to transform the information collected by the fleet management system and present it in a form valuable to the end users that are cargo oriented rather than just to the fleet operators who mind mostly about vehicles.

The data mining module was developed using the collected data directly as the input. Several complementary data mining techniques were researched and appropriate modules was developed regarding the discovery of data associations. Suitable pattern identification (unsupervised learning) algorithms evaluated (exploited) to provide adequate coverage of the range of temporal characteristics that system users would typically pay attention to. Parameters and specific annotated events used to built statistical models utilizing state of the art association algorithms resulting in a hybrid data mining module that leads to long-term predictions of predefined activities or events.

Moreover, visualization data techniques was integrated in order to enlighten temporal data patterns and

provide information in a robust and more efficient way than just showing a set of variables with correspondent values.

 

 

 

Traceability and Quality of Plant and Animal Production Products

 

This Application concerns the design, development and use of an innovative and extendable identification and traceability platform with multiple application capabilities in all sectors (fresh or not) of food and beverages.

 

Businesses through the electronic label will be able to collect and access huge amounts of information such as:

  1. the unique product code,
  2. the date of standardization,
  3. storage and transport conditions
  4. the history of locations
  5. conditions for the total product life.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

The project uses electronic, unique identification & tracking technologies to record traceability information on products. The platform will provide (a) business support and distribution decision support services and (b) services to the end consumer such as personalized product promotion.

The design, development and implementation of an innovative, intelligent and expandable system for discreet collection and recording on the final product critical to traceability but also the quality of parameters from the product life cycle (standardization, transfer and temporary storage before sale). The proposed system includes a set of cloud services connected to the end product that both end users have access to via the electronic tag and end users through the optical tag.

 

 

 

MeACT

 

The MeACT proposal aims to develop and validate new ICT-based ideas and approaches to empower and reward the guidance of citizens in need of guidance to create, improve and maintain a quality daily living environment. In addition, the proposed framework is expected to support active aging, as this will help improve the daily habits of citizens in a way that reflects the overall improvement in their lifestyle.

The goal of ensuring a high quality of human life requires the daily recording of all the parameters and habits that affect a person's well-being in the short and long term. This daily record is the key component of a more general plan for assessing living conditions, aiming at educating people to adopt a healthy lifestyle.

 

The technological advances that have been made have led to the implementation of systems that achieve great accuracy in recording a variety of physiological parameters that can be used to extract objective indicators that accurately outline the overall quality of life profile.

 

A back-end platform subsystem has been implemented to process the collected parameters for the purpose of extracting specialized information, knowledge discovery and decision support. In particular, the above bioparameters and indicators as well as elements of the individual file will be processed to draw conclusions and create recommendations for a person-centered healthy living environment. For this purpose, a service-oriented cloud system has been developed with the integration of mechanical learning algorithms and statistical models. The information produced, regarding the profile of the people under surveillance, is presented through smart mobile device applications for all recipients (users, specialized staff, etc.)

 

 

 

Hellenic Statistics Authority (ELSTAT)

In recent years, it has crystallized at a pan-European and global level need for combined use of geography with statistical information - since the Statistical information almost always contains a geographical dimension - as a tool for better decision making at local and national level. It has also been understood that the most detailed possible collection and mapping of geographical and statistics, with the upcoming 2021 population census being one first-class scope of the above.

At the same time, the tightness of financial resources Greece due to the economic crisis, leads to the search for solutions

that maximize the benefit and minimize the cost of collecting primary data.

 

The development of a software platform for the construction of geo-mentioned forms for conducting research on smart phones / tablets will be an essential tool for a more detailed and efficient performance of ELSTAT's statistical surveys.

 

The existing technological innovations and especially those of smartphones / tablets, of the internet services (web

services for both the dissemination and retrieval of data as well as geolocation capabilities and their integration into smartphones and tablets, allow the creation of applications that collect a very large amount of data on servers through applications that can run on the mobile of the user. In fact, with the latest GPS chipsets and signal reception from the combination of GPS and GLONASS systems, the location accuracy can reach up to ± 3 meters in areas where the signal reaches the receiver without problems. When the GPS signal is not available (eg in a high-density, high-rise urban area) the location can be detected with varying (and less) accuracy from mobile phone towers or local Wi-Fi networks, according to the literature. with the terminology Assisted GPS (A-GPS).

Of course, the interest of ELSTAT remains the utilization of the most accurate location (true GPS).

Potentially, the base of the above-mentioned addresses will be able to be a point of interest for other bodies / companies as it will be able to cover the Greek area universally.

 

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