Marco Ortolani's Outputs (28)

Extracting Structured Knowledge From Sensor Data for Hybrid Simulation (2014)
Book Chapter
Ortolani, M. (2014). Extracting Structured Knowledge From Sensor Data for Hybrid Simulation. In Advances onto the Internet of Things (153-165). Springer. https://doi.org/10.1007/978-3-319-03992-3_11

Obtaining continuous and detailed monitoring of indoor environments has today become viable, also thanks to the widespread availability of effective and flexible sensing technology; this paves the way for the design of practical Ambient Intelligence... Read More about Extracting Structured Knowledge From Sensor Data for Hybrid Simulation.

A Structural Approach to Infer Recurrent Relations in Data (2014)
Book Chapter
Cottone, P., Gaglio, S., & Ortolani, M. (2014). A Structural Approach to Infer Recurrent Relations in Data. In Advances onto the Internet of Things (105-119). Springer. https://doi.org/10.1007/978-3-319-03992-3_8

Extracting knowledge from a great amount of collected data has been a key problem in Artificial Intelligence during the last decades. In this context, the word “knowledge” refers to the non trivial new relations not easily deducible from the observat... Read More about A Structural Approach to Infer Recurrent Relations in Data.

Improving User Experience via Motion Sensors in an Ambient Intelligence Scenario (2013)
Conference Proceeding
Lo Re, G., Morana, M., & Ortolani, M. (2013). Improving User Experience via Motion Sensors in an Ambient Intelligence Scenario. In Proceedings of the 3rd International Conference on Pervasive Embedded Computing and Communication Systems PECCS (29-34). https://doi.org/10.5220/0004306000290034

Ambient Intelligence (AmI) is a new paradigm in Artificial Intelligence that aims at exploiting the information about the environment state in order to adapt it to the user preferences. AmI systems are usually based on several cheap and unobtrusive s... Read More about Improving User Experience via Motion Sensors in an Ambient Intelligence Scenario.

Gesture Recognition for Improved User Experience in a Smart Environment (2013)
Conference Proceeding
Gaglio, S., Lo Re, G., Morana, M., & Ortolani, M. (2013). Gesture Recognition for Improved User Experience in a Smart Environment. In AI*IA 2013: Advances in Artificial Intelligence (493-504). https://doi.org/10.1007/978-3-319-03524-6_42

Ambient Intelligence (AmI) is a new paradigm that specifically aims at exploiting sensory and context information in order to adapt the environment to the user’s preferences; one of its key features is the attempt to consider common devices as an int... Read More about Gesture Recognition for Improved User Experience in a Smart Environment.

User activity recognition for energy saving in smart homes (2013)
Presentation / Conference
Cottone, P., Gaglio, S., Re, G. L., & Ortolani, M. (2013, October). User activity recognition for energy saving in smart homes. Paper presented at 2013 Sustainable Internet and ICT for Sustainability (SustainIT), Palermo, Italy

QoS-Aware Fault Detection in Wireless Sensor Networks (2013)
Journal Article
De Paola, A., Lo Re, G., Milazzo, F., & Ortolani, M. (2013). QoS-Aware Fault Detection in Wireless Sensor Networks. International Journal of Distributed Sensor Networks, https://doi.org/10.1155/2013/165732

Wireless sensor networks (WSNs) are a fundamental building block of many pervasive applications. Nevertheless the use of such technology raises new challenges regarding the development of reliable and fault-tolerant systems. One of the most critical... Read More about QoS-Aware Fault Detection in Wireless Sensor Networks.

Mimicking biological mechanisms for sensory information fusion (2013)
Journal Article
De Paola, A., La Cascia, M., Lo Re, G., Morana, M., & Ortolani, M. (2013). Mimicking biological mechanisms for sensory information fusion. Biologically Inspired Cognitive Architectures, 3, 27-38. https://doi.org/10.1016/j.bica.2012.09.002

An Innovative System for Vineyard Management in Sicily (2010)
Journal Article
Ortolani. (2010). An Innovative System for Vineyard Management in Sicily. Journal of Agricultural Engineering, https://doi.org/10.4081/jae.2010.1.13

The aim of this study was to monitor the micro-climate of the grapevine in order to detect the adversities of the spring period (especially April and May), while reducing the operating costs of the vineyard, and increasing the overall quality of grap... Read More about An Innovative System for Vineyard Management in Sicily.