Non-Destructive Control of Qualitative Characteristics of Fruits Using Radioelectronics

В данной работе представлены неразрушающие методы определения качественных характеристик различных фруктов и овощей. Все исследованные методы предназначены для определения соотношений физических параметров фрукта или овоща и его качества, например, зрелости или цвета. Использован метод измерения S-параметров для исследования характеристик яблока. Представлены измерения коэффициента отражения яблока при помощи баночной антенны.This paper presents non-destructive methods for determining the qualitative characteristics of various fruits and vegetables. All the methods investigated try to find and determine how the physical parameters of a fruit or vegetable relate to its quality, such as ripeness or color. The method of measuring S-parameters was used to study the characteristics of an apple. Measurements of the reflection coefficient of an apple using a canned antenna are presented

Wi-Fi Sensing: Applications and Challenges

Wi-Fi technology has strong potentials in indoor and outdoor sensing applications, it has several important features which makes it an appealing option compared to other sensing technologies. This paper presents a survey on different applications of Wi-Fi based sensing systems such as elderly people monitoring, activity classification, gesture recognition, people counting, through the wall sensing, behind the corner sensing, and many other applications. The challenges and interesting future directions are also highlighted

Winect: 3D Human Pose Tracking for Free-form Activity Using Commodity WiFi

WiFi human sensing has become increasingly attractive in enabling emerging human-computer interaction applications. The corresponding technique has gradually evolved from the classification of multiple activity types to more fine-grained tracking of 3D human poses. However, existing WiFi-based 3D human pose tracking is limited to a set of predefined activities. In this work, we present Winect, a 3D human pose tracking system for free-form activity using commodity WiFi devices. Our system tracks free-form activity by estimating a 3D skeleton pose that consists of a set of joints of the human body. In particular, we combine signal separation and joint movement modeling to achieve free-form activity tracking. Our system first identifies the moving limbs by leveraging the two-dimensional angle of arrival of the signals reflected off the human body and separates the entangled signals for each limb. Then, it tracks each limb and constructs a 3D skeleton of the body by modeling the inherent relationship between the movements of the limb and the corresponding joints. Our evaluation results show that Winect is environment-independent and achieves centimeter-level accuracy for free-form activity tracking under various challenging environments including the none-line-of-sight (NLoS) scenarios

Wi-Fi Sensing: Applications and Challenges

Wi-Fi technology has strong potentials in indoor and outdoor sensing applications, it has several important features which makes it an appealing option compared to other sensing technologies. This paper presents a survey on different applications of Wi-Fi-based sensing systems such as elderly people monitoring, activity classification, gesture recognition, people counting, through the wall sensing, behind the corner sensing, and many other applications. The challenges and interesting future directions are also highlighted

Moisture estimation for precision agriculture through RF sensing

Convenient, non-obtrusive, low-cost, and accurate sensing of fruit moisture content is crucial for the scientific studies of Pomology and Viticulture and their associated agriculture. It can provide early indicators of yield estimation and crop health as well as providing data for food production and precision farming systems. With a focus on grapes, we introduce SING, a scheme that senses grape moisture content by utilizing RF signals but without physical contact with the fruit. In this thesis, we extend the investigation of the theoretical relationship between the dielectric properties and the moisture content of agricultural products to establish a sensing model in the 5 GHz band. To make the work practical, we are first to measure the dielectric properties of grape bunches (not individually as that would be destructive), presenting a unique measurement challenge as internal grapes are hidden. In doing so, we demonstrate that our technique precisely estimates moisture content to a high degree of accuracy (90%). Current RF sensing models to estimate moisture are destructive; they require samples to be constrained in containers. Our work is first to dispense with such impracticalities, and, without contact with the object, accurately measures non-uniform grape clusters in open space. We demonstrate that SING is superior to existing work in its ability to accurately measure the dielectric properties of non-uniform fruit objects and test this through both lab-based experimentation and preliminary outdoor vineyard tests. We also examine the transferability of SING’s approach to real-world scenarios.Open Acces