Rural development and communication: a community media project in Uttar Pradesh (India)

Loaded with 16% of the world’s population, India is a challenged country. More than a third of its citizens live below the poverty line - on less than a dollar a day. These people have no proper electricity, no proper drinking water supply, no proper sanitary facilities and well over 40% are illiterates. More than 65% live in rural areas and 60% earn their livelihood from agriculture. Only a meagre 3.63% have access to telephone and less than 1% have access to a computer. Therefore, providing access to timely information on agriculture, weather, social, health care, employment, fishing, is of utmost importance to improve the conditions of rural poor. After some introductive chapters, whose function is to provide a comprehensive framework – both theoretical and practical – of the current rural development policies and of the media situation in India and Uttar Pradesh, my dissertation presents the findings of the pilot project entitled “Enhancing development support to rural masses through community media activity”, launched in 2005 by the Department of Mass Communication and Journalism of the Faculty of Arts of the University of Lucknow (U.P.) and by the local NGO Bharosa. The project scope was to involve rural people and farmers from two villages of the district of Lucknow (namely Kumhrava and Barhi Gaghi) in a three-year participatory community media project, based on the creation, implementation and use of a rural community newspaper and a rural community internet centre. Community media projects like this one have been rarely carried out in India because the country has no proper community media tradition: therefore the development of the project has been a challenge for the all stakeholders involved.

Intelligent Sensor Systems for Structural Health Monitoring Applications

The convergence between the recent developments in sensing technologies, data science, signal processing and advanced modelling has fostered a new paradigm to the Structural Health Monitoring (SHM) of engineered structures, which is the one based on intelligent sensors, i.e., embedded devices capable of stream processing data and/or performing structural inference in a self-contained and near-sensor manner. To efficiently exploit these intelligent sensor units for full-scale structural assessment, a joint effort is required to deal with instrumental aspects related to signal acquisition, conditioning and digitalization, and those pertaining to data management, data analytics and information sharing. In this framework, the main goal of this Thesis is to tackle the multi-faceted nature of the monitoring process, via a full-scale optimization of the hardware and software resources involved by the {SHM} system. The pursuit of this objective has required the investigation of both: i) transversal aspects common to multiple application domains at different abstraction levels (such as knowledge distillation, networking solutions, microsystem {HW} architectures), and ii) the specificities of the monitoring methodologies (vibrations, guided waves, acoustic emission monitoring). The key tools adopted in the proposed monitoring frameworks belong to the embedded signal processing field: namely, graph signal processing, compressed sensing, ARMA System Identification, digital data communication and TinyML.