Privacy-enhancing Aggregation of Internet of Things Data via Sensors Grouping

Big data collection practices using Internet of Things (IoT) pervasive technologies are often privacy-intrusive and result in surveillance, profiling, and discriminatory actions over citizens that in turn undermine the participation of citizens to the development of sustainable smart cities. Nevertheless, real-time data analytics and aggregate information from IoT devices open up tremendous opportunities for managing smart city infrastructures. The privacy-enhancing aggregation of distributed sensor data, such as residential energy consumption or traffic information, is the research focus of this paper. Citizens have the option to choose their privacy level by reducing the quality of the shared data at a cost of a lower accuracy in data analytics services. A baseline scenario is considered in which IoT sensor data are shared directly with an untrustworthy central aggregator. A grouping mechanism is introduced that improves privacy by sharing data aggregated first at a group level compared as opposed to sharing data directly to the central aggregator. Group-level aggregation obfuscates sensor data of individuals, in a similar fashion as differential privacy and homomorphic encryption schemes, thus inference of privacy-sensitive information from single sensors becomes computationally harder compared to the baseline scenario. The proposed system is evaluated using real-world data from two smart city pilot projects. Privacy under grouping increases, while preserving the accuracy of the baseline scenario. Intra-group influences of privacy by one group member on the other ones are measured and fairness on privacy is found to be maximized between group members with similar privacy choices. Several grouping strategies are compared. Grouping by proximity of privacy choices provides the highest privacy gains. The implications of the strategy on the design of incentives mechanisms are discussed

Assessment of the Can Bus Technology Implemented on Modern Agricultural Tractors to Study Fuel Consumption Savings

In developed countries, the mechanized agriculture is highly dependent on fuel. Unfortunately, the heterogeneity and complexity inherent to agricultural process do not help the actors (researchers, counselors, farmers) to improve fuel consumption efficiency in the farms. In order to measure precisely the use of the tractors this study proposes to rely on the embedded CAN bus technology and RTK positioning system implementing modern tractors to record fully characterized data of the engine load. This study demonstrates the feasibility of such proposition by testing specific dataloggers and software in-situ and by decoding signals to data and characterizing them

The inspection of soil-disinfection equipment in Belgium.

In Belgium, the mandatory inspection of field and orchard sprayers was already started up in 1995. At that time, there were only inspection protocols available for those two types of sprayers. From 2008 on, two new inspection protocols were developed: one for greenhouse sprayers and one for soil-disinfection machines. Those inspection protocols were added to the Belgian legislation and implemented since 2011. The inspection protocol for greenhouse sprayers was mainly based on the two existing protocols (field and orchard sprayers) as the working principle of those machines was similar.Soil disinfection machines used on Belgian territory needed another approach because of the differences in pressurising and application technique compared to classical spraying machines. Soil disinfection machines use a closed tank containing the vaporous disinfectant. The tank is pressurised by a compressor or a diving cylinder. As concerns the injector side of those machines there are different possibilities. Some are using a manifold with restrictor plates or a small tap per injector, others use narrow tubes towards the injectors, and sometimes nozzles are used. As one can see, there are no standard inspection methods available for those types of machines. Neither a standard spray pattern measurement, nor a separate pressure and nozzle testing is possible on most of those machines. On top there are some important safety aspects that need special attention due to the hazardous products used. The Belgian inspection protocol was almost completely developed in-house and makes it possible to inspect soil-disinfection machines in an accurate, safe and economical way

The Belgian experience with sprayer inspection activities and future challenges

In Belgium, the mandatory inspection of field crop, orchard and vineyard sprayers was already started up in 1995. Furthermore, the inspection of greenhouse sprayers and soil-disinfection machines was implemented respectively in 2011 and 2014. So Belgium can look back on more than 22 years of experiences with the inspection of sprayers.In Belgium, the mandatory inspection of field crop, orchard and vineyard sprayers was already started up in 1995. Furthermore, the inspection of greenhouse sprayers and soil-disinfection machines was implemented respectively in 2011 and 2014. So Belgium can look back on more than 22 years of experiences with the inspection of sprayers

Impact of base dataset design on few-shot image classification

The quality and generality of deep image features is crucially determined by the data they have been trained on, but little is known about this often overlooked effect. In this paper, we systematically study the effect of variations in the training data by evaluating deep features trained on different image sets in a few-shot classification setting. The experimental protocol we define allows to explore key practical questions. What is the influence of the similarity between base and test classes? Given a fixed annotation budget, what is the optimal trade-off between the number of images per class and the number of classes? Given a fixed dataset, can features be improved by splitting or combining different classes? Should simple or diverse classes be annotated? In a wide range of experiments, we provide clear answers to these questions on the miniImageNet, ImageNet and CUB-200 benchmarks. We also show how the base dataset design can improve performance in few-shot classification more drastically than replacing a simple baseline by an advanced state of the art algorithm.Comment: 23 pages, 11 figures, to appear in ECCV 202