Informatica

Smart Farming (SF) has garnered interest from computer science researchers for its potential to address challenges in Smart Farming and Precision Agriculture (PA). This systematic review explores the application of Fuzzy Logic (FL) in these areas. Using a specific anonymous search method across five scientific web indexing databases, we identified relevant scholarly articles published from 2017 to 2024, assessed through the PRISMA methodology. Out of 830 selected papers, the review revealed four gaps in using FL to manage imprecise data in Smart Farming. This review provides valuable insights into FL for potential applications and areas needing further investigation in SF.

Relational mathematics, as it is studied in fields like mathematical economics and social choice theory for some time, provides a rich and general framework and appears to be a natural and direct way to paraphrase optimization goals, to represent user preferences, to justify fairness criterions, to cope with QoS or to valuate utility. Here, we will focus on the specific application aspects of formal relations in network design and control problems and provide the general concept of relational optimization. In relational optimization, we represent the optimization problem by a formal relation, and the solution by the set of maximal (or non-dominated) elements of this relation. This appears to be a natural extension of standard optimization, and covers other notions of optimality as well. Along with this, we will provide a set of fairness relations that can serve as maximizing relations in relational optimization according to various application needs, and we specify a meta-heuristic approach derived from evolutionary multi-objective optimization algorithms to approximate their maximum sets.