Riqualificare la residenza sociale, rione Pilastro, Bologna

Il complesso residenziale “Pilastro” costruito tra il 1962 e il 1985 si trova a Bologna, a nord del quartiere San Donato, oltre la linea tracciata dalla tangenziale e si è costituito in tre fasi, corrispondenti ai tre comparti di intervento: il nucleo di prima realizzazione, il “Virgolone” e le torri. Il tema affrontato in questa tesi, elaborato all’interno del laboratorio di sintesi finale Architettura sostenibile, riguarda la definizione di strategie di intervento per la riqualificazione del comparto di “Primo impianto” che attualmente presenta molteplici criticità: - debole coesione sociale ed episodi di disagio e micro-criminalità - inadeguatezza sismica - scarse prestazioni energetiche degli edifici Il progetto si è proposto l’obbiettivo di ricucire e rifunzionalizzare l’intero comparto, investendo in modo integrato gli aspetti urbanistico, architettonico e tecnologico, in modo da influire positivamente sulle condizioni socio-economiche dell’insediamento

A Modular Aerial Vehicle with Redundant Actuation

Abstract-This work presents the design and experimental validation of a control strategy for an innovative modular aerial vehicle characterized by redundant actuation. For this class of aircraft, the distinguishing feature of the proposed design -which sets it apart from standard vertical take-off and landing (VTOL) under-actuated configurations such as helicopters, ducted-fan tail-sitters or multi-rotors -is that the input redundancy can be employed to improve the dynamical properties of the system. In particular, the vehicle performance can be enhanced in certain applications that benefit from a larger number of degrees of freedom being simultaneously controlled. A control strategy is proposed which is capable of globally stabilizing the dynamics of this class of vehicles along a desired trajectory. The methodology is validated by means of experiments carried out on a special prototype obtained by rigidly connecting two ducted-fan tail-sitter UAVs

Assessing the Feasibility of Augmenting Fall Detection Systems by Relying on UWB-Based Position Tracking and a Home Robot

Falls in the home environment are a primary cause of injury in older adults. According to the U.S. Centers for Disease Control and Prevention, every year, one in four adults 65 years of age and older reports experiencing a fall. A variety of different technologies have been proposed to detect fall events. However, the need to detect all fall instances (i.e., to avoid false negatives) has led to the development of systems marked by high sensitivity and hence a significant number of false alarms. The occurrence of false alarms causes frequent and unnecessary calls to emergency response centers, which are critical resources that should be utilized only when necessary. Besides, false alarms decrease the level of confidence of end-users in the fall detection system with a negative impact on their compliance with using the system (e.g., wearing the sensor enabling the detection of fall events). Herein, we present a novel approach aimed to augment traditional fall detection systems that rely on wearable sensors and fall detection algorithms. The proposed approach utilizes a UWB-based tracking system and a home robot. When the fall detection system generates an alarm, the alarm is relayed to a base station that utilizes a UWB-based tracking system to identify where the older adult and the robot are so as to enable navigating the environment using the robot and reaching the older adult to check if he/she experienced a fall. This approach prevents unnecessary calls to emergency response centers while enabling a tele-presence using the robot when appropriate. In this paper, we report the results of a novel fall detection algorithm, the characteristics of the alarm notification system, and the accuracy of the UWB-based tracking system that we implemented. The fall detection algorithm displayed a sensitivity of 99.0% and a specificity of 97.8%. The alarm notification system relayed all simulated alarm notification instances with a maximum delay of 106 ms. The UWB-based tracking system was found to be suitable to locate radio tags both in line-of-sight and in no-line-of-sight conditions. This result was obtained by using a machine learning-based algorithm that we developed to detect and compensate for the multipath effect in no-line-of-sight conditions. When using this algorithm, the error affecting the estimated position of the radio tags was smaller than 0.2 m, which is satisfactory for the application at hand