Modelling e-participation implementation:A network-based approach for online and offline participation

E-participation consists of several phases such as planning, implementation and evaluation. However, when representing this process, the implementation phase tends to be considered as a single block (the so-called "black-box"). This becomes a problem when the implementation combines offline and online methods, as it requires a detailed characterization and representation of all elements involved. In this paper we tackle this issue by proposing a network-based model to describe these methods. This choice is motivated by the fact that network models allow to better describe the distributed nature of these activities. To build this model we make use of the theory in Social Networks Analysis (SNA) to represent the main interactions between all actors involved. To asses the reliability and added value of the presented model, this approach is applied to four different use cases that showcase various combinations of online and offline participation methods. The results of these use cases show the great potential of the network-based model as a tool for designing, comparing and evaluating different types of implementations. Namely, the visualization of the model allows to asses the level of participation, the role of the different actors and how different instruments are combined

Modelling e-participation implementation:A network-based approach for online and offline participation

E-participation consists of several phases such as planning, implementation and evaluation. However, when representing this process, the implementation phase tends to be considered as a single block (the so-called "black-box"). This becomes a problem when the implementation combines offline and online methods, as it requires a detailed characterization and representation of all elements involved. In this paper we tackle this issue by proposing a network-based model to describe these methods. This choice is motivated by the fact that network models allow to better describe the distributed nature of these activities. To build this model we make use of the theory in Social Networks Analysis (SNA) to represent the main interactions between all actors involved. To asses the reliability and added value of the presented model, this approach is applied to four different use cases that showcase various combinations of online and offline participation methods. The results of these use cases show the great potential of the network-based model as a tool for designing, comparing and evaluating different types of implementations. Namely, the visualization of the model allows to asses the level of participation, the role of the different actors and how different instruments are combined

Smart Testing and Selective Quarantine for the Control of Epidemics

This paper is based on the observation that, during Covid-19 epidemic, the choice of which individuals should be tested has an important impact on the effectiveness of selective confinement measures. This decision problem is closely related to the problem of optimal sensor selection, which is a very active research subject in control engineering. The goal of this paper is to propose a policy to smartly select the individuals to be tested. The main idea is to model the epidemics as a stochastic dynamic system and to select the individual to be tested accordingly to some optimality criteria, e.g. to minimize the probability of undetected asymptomatic cases. Every day, the probability of infection of the different individuals is updated making use of the stochastic model of the phenomenon and of the information collected in the previous days. Simulations for a closed community of 10000 individuals show that the proposed technique, coupled with a selective confinement policy, can reduce the spread of the disease while limiting the number of individuals confined if compared to the simple contact tracing of positive and to an off-line test selection strategy based on the number of contacts.Comment: Preprint submitted to Annual Reviews in Control. Updated on 22 December 202

Information-Driven Path Planning for UAV with Limited Autonomy in Large-scale Field Monitoring

This paper presents a novel information-based mission planner for a drone tasked to monitor a spatially distributed dynamical phenomenon. For the sake of simplicity, the area to be monitored is discretized. The insight behind the proposed approach is that, thanks to the spatio-temporal dependencies of the observed phenomenon, one does not need to collect data on the entire area. In fact, unmeasured states can be estimated using an estimator, such as a Kalman filter. In this context the planning problem becomes the one of generating a flight path that maximizes the quality of the state estimation while satisfying the flight constraints (e.g. flight time). The first result of this paper is to formulate this problem as a special Orienteering Problem where the cost function is a measure of the quality of the estimation. This approach provides a Mixed-Integer Semi-Definite formulation to the problem which can be optimally solved for small instances. For larger instances, two heuristics are proposed which provide good sub-optimal results. To conclude, numerical simulations are shown to prove the capabilities and efficiency of the proposed path planning strategy. We believe this approach has the potential to increase dramatically the area that a drone can monitor, thus increasing the number of applications where monitoring with drones can become economically convenient

Active monitoring of large-scale phenomena

This thesis focuses on the development of monitoring strategies suited for large-scale processes where the amount of resources available for the sensing is a critical limitation. The proposed approach consists in planning simultaneously the gathering of the data and its usage. This approach allows to optimize the information obtained given the limited resources. This thesis presents a general methodology composed of 3 steps: modelling, estimation, and monitoring planning. The theoretical developments presented in this dissertation are divided into two separated parts that focus on two macro-classes of systems that enclose the vast majority of possible large-scale monitored phenomena. The relevance and effectiveness of the results of this thesis are demonstrated with the help of some case studies, such as: soil-plant water dynamics, epidemics spreading and pest populations. Given the depth of the study concerning the monitoring of pest populations, this application is presented as a separated third part of this dissertation.Doctorat en Sciences de l'ingénieur et technologieinfo:eu-repo/semantics/nonPublishe

Carrier-vehicle system for delivery in city environments

info:eu-repo/semantics/publishe