This preliminary study explores the use of a smart tray prototype equipped with a weight sensor to analyze consumer eating behavior in real-life conditions. Conducted in 2022, at the restaurant “La Confluence” in Namur, with 60 participants, the experiment involved tracking the progression of a standardized meal, “Scallops in sauce with vegetables”. The collected data allowed for the calculation of variables such as bite count, applied force, meal duration, and quantity consumed. Through mathematical processing, insights into individual and group eating patterns were developed, with 39 usable datasets analyzed. Our first results show that the smart tray is capable of estimating the weight consumed and the number of bites with over 97% accuracy. Statistical analysis enabled the identification of four distinct groups of individuals based on five behavioral variables related to eating behavior. The smart tray could be used in hospitality establishments including cafeterias, restaurants, or brasseries, where it could serve as a valuable tool for monitoring meal nutrition. Further improvements will aim to enhance utensil and action recognition through artificial intelligence, which will also support a more detailed characterization of eating behavior.

This paper presents and compares two different solution approaches to optimize the glass collection process at a single intermunicipal authority in Belgium. First, a model enhancement approach is proposed to solve a shift scheduling optimization problem integrating the construction of glass collection routes. Second, a simulation based rolling horizon procedure is designed to determine the possible benefits of providing the glass containers with fill level sensors. The performance of both solution approaches is evaluated and compared using real-life data.

The purpose of this paper is to illustrate the use of statistical techniques to evaluate the effectiveness of voluntary policy instruments for waste management. The voluntary character of these instruments implies that latent characteristics, unobserved by the analyst, might influence the participation decision and might lead to biased estimates of the effectiveness of the policy instrument if standard techniques are used. We propose an extension of the Difference-in-Differences estimator to evaluate the effectiveness of voluntary policy instruments. We illustrate the technique by estimating the effectiveness of voluntary cooperation agreements between the Flemish environmental administration and individual municipalities. We focus on agreements which aim at curbing residential solid waste. Using a dataset covering all 308 Flemish municipalities for the period 2000-2005, our results indicate that municipalities subscribing to the agreement reduced their waste level by less than what could be expected on the basis of their own performance prior to subscription and the performance of the non-subscribers. This result might be explained by rising marginal cost of extra residential solid waste reduction policies. In addition, there are indications that subscribing municipalities refrain from additional reduction efforts once the target waste level of the program is achieved.