Virtual sensing technology applied to a swarm of autonomous robots.

This thesis proposes a novel technology in the field of swarm robotics that allows a swarm of robots to sense a virtual environment through virtual sensors. Virtual sensing is a desirable and helpful technology in swarm robotics research activity, because it allows the researchers to efficiently and quickly perform experiments otherwise more expensive and time consuming, or even impossible. In particular, we envision two useful applications for virtual sensing technology. On the one hand, it is possible to prototype and foresee the effects of a new sensor on a robot swarm, before producing it. On the other hand, thanks to this technology it is possible to study the behaviour of robots operating in environments that are not easily reproducible inside a lab for safety reasons or just because physically infeasible. The use of virtual sensing technology for sensor prototyping aims to foresee the behaviour of the swarm enhanced with new or more powerful sensors, without producing the hardware. Sensor prototyping can be used to tune a new sensor or perform performance comparison tests between alternative types of sensors. This kind of prototyping experiments can be performed through the presented tool, that allows to rapidly develop and test software virtual sensors of different typologies and quality, emulating the behaviour of several hardware real sensors. By investigating on which sensors is better to invest, a researcher can minimize the sensors’ production cost while achieving a given swarm performance. Through augmented reality, it is possible to test the performance of the swarm in a desired virtual environment that cannot be set into the lab for physical, logistic or economical reasons. The virtual environment is sensed by the robots through properly designed virtual sensors. Virtual sensing technology allows a researcher to quickly carry out real robots experiment in challenging scenarios without all the required hardware and environment.

Work environments implementation for genomic reporting and analytics

A global italian pharmaceutical company has to provide two work environments that favor different needs. The environments will allow to develop solutions in a controlled, secure and at the same time in an independent manner on a state-of-the-art enterprise cloud platform. The need of developing two different environments is dictated by the needs of the working units. Indeed, the first environment is designed to facilitate the creation of application related to genomics, therefore, designed more for data-scientists. This environment is capable of consuming, producing, retrieving and incorporating data, furthermore, will support the most used programming languages for genomic applications (e.g., Python, R). The proposal was to obtain a pool of ready-togo Virtual Machines with different architectures to provide best performance based on the job that needs to be carried out. The second environment has more of a traditional trait, to obtain, via ETL (Extract-Transform-Load) process, a global datamodel, resembling a classical relational structure. It will provide major BI operations (e.g., analytics, performance measure, reports, etc.) that can be leveraged both for application analysis or for internal usage. Since, both architectures will maintain large amounts of data regarding not only pharmaceutical informations but also internal company informations, it would be possible to digest the data by reporting/ analytics tools and also apply data-mining, machine learning technologies to exploit intrinsic informations. The thesis work will introduce, proposals, implementations, descriptions of used technologies/platforms and future works of the above discussed environments.

Development and testing of a virtual energy meter using the Labview Environment

The quantity of electric energy utilized by a home, a business, or an electrically powered device is measured by an electricity meter, also known as an electric meter, electrical meter, or energy meter. Electric meters located at customers' locations are used by electric providers for billing. They are usually calibrated in billing units, with the kilowatt hour being the most popular (kWh). Typically, they are read once each billing cycle. When energy savings are sought during specific times, some meters may monitor demand, or the highest amount of electricity used during a specific time. Additionally, some meters feature relays for load shedding in response to responses during periods of peak load. The amount of electrical energy consumed by users is measured by a Watt-hour meter, also known as an energy meter. To charge the electricity usage by loads like lights, fans, and other appliances, utilities put these gadgets everywhere, including in households, businesses, and organizations. Watts are a fundamental power unit. A kilowatt is equal to one thousand watts. One kilowatt is regarded as one unit of energy used if used for one hour. These meters calculate the product of the instantaneous voltage and current readings and provide instantaneous power. This power is distributed over a period and is used during that time. Depending on the supply used by home or commercial installations, these may be single or three phase meters. These can be linked directly between line and load for minor service measurements, such as home consumers. However, step-down current transformers must be installed for greater loads to handle their higher current demands.