“My personal forecast”: the digital transformation of the weather forecast communication using a fuzzy logic recommendation system

Abstract

Abstract. Communicating the scientific data of the weather forecasts to the general public has always been a challenge. Using computer graphics' visual representations to convey the message to average people has certainly helped a lot to popularize the weather forecast consumption by the general public. However, these representations are not information rich since they are abstractions; moreover they are not very actionable on the receiver side to help one decide how s/he will “live” the forecast weather conditions and prepare appropriately. Therefore, there is a need to personalize the forecast based on past experience of the individuals and their personal needs. The forecast has to become more human- and needs-oriented and more focused to the particular requirements of each individual person. We, thus, propose a new co-creation process in which the audience is called to provide a daily feedback on how they lived the weather conditions personally on a daily basis, so that, “my personal forecast” can be produced making the forecast more actionable on the user side. Preliminary such attempts focused solely on the “feels like” temperature forecasts. To arrive at the “my personal forecast”, artificial intelligence based recommender systems need to be applied, using fuzzy logic as the appropriate method for the user to express the individually perceived weather conditions.

Optimal Update Times for Stale Information Metrics Including the Age of Information

“…As mentioned above, there are many applications that face this problem. Such applications include: updating automobile traffic information [7], when to repeat a measurement of atmospheric data for weather forecasting [8]; determining the optimal time to update routing tables in data networks [9]; when to update medical testing (such as cancer screenings, mammograms, infectious disease testing such as COVID-19 tests, etc.) [10]; updating stock prices [11]; updating a transaction database [12]; updating data regarding a security or surveillance system [13]; updating cached pages [14]; refreshing website data [15]; updating the relative position of drones in a swarm [16]; updating measures of reputation [17]; status update policies under an energy harvesting setting [4] [5] [6]; and many more.…”