Search results for " sensor"

A Survey on LoRa for Smart Agriculture: Current Trends and Future Perspectives

2023

This paper provides a survey on the adoption of LoRa in the agricultural field, and reviews state-of-the-art solutions for Smart Agriculture, analyzing the potential of this technology in different infield applications. In particular, we consider four reference scenarios, namely irrigation systems, plantation and crop monitoring, tree monitoring, and livestock monitoring, which exhibit heterogeneous requirements in terms of network bandwidth, density, sensors’ complexity, and energy demand, as well as latency in the decision process. We discuss how LoRa-based solutions can work in these scenarios, analyzing their scalability, interoperability, network architecture, and energy-efficiency. Fi…

MRAS Sensorless Techniques for High Performance Linear Induction Motor Drives.

2010

This paper proposes an MRAS (Model reference Adaptive System) speed observer suited for linear induction motors (LIM). Starting from the dynamical equation of the LIM in the synchronous reference frame in literature, the so-called voltage and current models of the LIM in the stationary reference frame, taking into consideration the end effects, have been deduced. These equations have been used respectively as reference and adaptive model of an MRAS observer. As machine under test, a complete dynamic model, based on the constructive elements of the LIM and taking into consideration the end effects by the definition of a proper air-gap function, has been adopted. This model has been previousl…

Sensorless interaction robot control

2010

Vector Projection-based Sensorless Control of a SynRM Drive Including Self and Cross-Saturation

2022

This paper presents a sensorless technique for SynRM drives that is based on a vector projection method and takes into consideration the magnetic saturation of the motor, both the self and the cross-saturation. The proposed method is based on the dynamic equation of the SynRM including saturation, rewritten in integral form, and does not involve any high-frequency carrier injection. The technique has been tested in numerical simulation and experimentally on a suitably developed test set-up. Experimental results show a correct behavior of the sensorless SynRM drive, properly accomplishing speed transients in a wide speed range, including low speed, still maintaining a good accuracy in the sp…

Soft Sensor Design, Transferability and Causality through Machine Learning Techniques

2023

Prnu Pattern Alignment for Images and Videos Based on Scene Content

2019

This paper proposes a novel approach for registering the PRNU pattern between different camera acquisition modes by relying on the imaged scene content. First, images are aligned by establishing correspondences between local descriptors: The result can then optionally be refined by maximizing the PRNU correlation. Comparative evaluations show that this approach outperforms those based on brute-force and particle swarm optimization in terms of reliability, accuracy and speed. The proposed scene-based approach for PRNU pattern alignment is suitable for video source identification in multimedia forensics applications.

Adaptable data models for scalable Ambient Intelligence scenarios

2011

In most real-life scenarios for Ambient Intelligence, the need arises for scalable simulations that provide reliable sensory data to be used in the preliminary design and test phases. This works present an approach to modeling data generated by a hybrid simulator for wireless sensor networks, where virtual nodes coexist with real ones. We apply our method to real data available from a public repository and show that we can compute reliable models for the quantities measured at a given reference site, and that such models are portable to different environments, so as to obtain a complete, scalable and reliable testing environment.

An Ambient Intelligence Architecture for Extracting Knowledge from Distributed Sensors

2009

Precisely monitoring the environmental conditions is an essential requirement for AmI projects, but the wealth of data generated by the sensing equipment may easily overwhelm the modules devoted to higher-level reasoning, clogging them with irrelevant details. The present work proposes a new approach to knowledge extraction from raw data that addresses this issue at different levels of abstraction. Wireless sensor networks are used as the pervasive sensory tool, and their computational capabilities are exploited to remotely perform preliminary data processing. A central intelligent unit subsequently extracts higher-level concepts represented in a geometrical space and carries on symbolic re…

Exploiting the Human Factor in a WSN-Based System for Ambient Intelligence

2009

Practical applications of ambient intelligence cannot leave aside requirements about ubiquity, scalability, and transparency to the user. An enabling technology to comply with this goal is represented by wireless sensor networks (WSNs); however, although capable of limited in-network processing, they lack the computational power to act as a comprehensive intelligent system. By taking inspiration from the sensory processing model of complex biological organisms, we propose here a cognitive architecture able to perceive, decide upon, and control the environment of which the system is part. WSNs act as a transparent interface that allows the system to understand human requirements through impl…

Design of an Adaptive Bayesian System for Sensor Data Fusion

2014

Many artificial intelligent systems exploit a wide set of sensor devices to monitor the environment. When the sensors employed are low-cost, off-the-shelf devices, such as Wireless Sensor Networks (WSN), the data gathered through the sensory infrastructure may be affected by noise, and thus only partially correlated to the phenomenon of interest. One way of overcoming these limitations might be to adopt a high-level method to perform multi-sensor data fusion. Bayesian Networks (BNs) represent a suitable tool for performing refined artificial reasoning on heterogeneous sensory data, and for dealing with the intrinsic uncertainty of such data. However, the configuration of the sensory infrast…