Prediction of Pest Insect Appearance Using Sensors and Machine Learning.

The appearance of pest insects can lead to a loss in yield if farmers do not respond in a timely manner to suppress their spread. Occurrences and numbers of insects can be monitored through insect traps, which include their permanent touring and checking of their condition. Another more efficient way is to set up sensor devices with a camera at the traps that will photograph the traps and forward the images to the Internet, where the pest insect's appearance will be predicted by image analysis. Weather conditions, temperature and relative humidity are the parameters that affect the appearance of some pests, such as Helicoverpa armigera. This paper presents a model of machine learning that can predict the appearance of insects during a season on a daily basis, taking into account the air temperature and relative humidity. Several machine learning algorithms for classification were applied and their accuracy for the prediction of insect occurrence was presented (up to 76.5%). Since the data used for testing were given in chronological order according to the days when the measurement was performed, the existing model was expanded to take into account the periods of three and five days. The extended method showed better accuracy of prediction and a lower percentage of false detections. In the case of a period of five days, the accuracy of the affected detections was 86.3%, while the percentage of false detections was 11%. The proposed model of machine learning can help farmers to detect the occurrence of pests and save the time and resources needed to check the fields.

Semiconductor Gas Sensors: Materials, Technology, Design, and Application.

This paper presents an overview of semiconductor materials used in gas sensors, their technology, design, and application. Semiconductor materials include metal oxides, conducting polymers, carbon nanotubes, and 2D materials. Metal oxides are most often the first choice due to their ease of fabrication, low cost, high sensitivity, and stability. Some of their disadvantages are low selectivity and high operating temperature. Conducting polymers have the advantage of a low operating temperature and can detect many organic vapors. They are flexible but affected by humidity. Carbon nanotubes are chemically and mechanically stable and are sensitive towards NO and NH3, but need dopants or modifications to sense other gases. Graphene, transition metal chalcogenides, boron nitride, transition metal carbides/nitrides, metal organic frameworks, and metal oxide nanosheets as 2D materials represent gas-sensing materials of the future, especially in medical devices, such as breath sensing. This overview covers the most used semiconducting materials in gas sensing, their synthesis methods and morphology, especially oxide nanostructures, heterostructures, and 2D materials, as well as sensor technology and design, application in advance electronic circuits and systems, and research challenges from the perspective of emerging technologies.

Convective Drying of Fresh and Frozen Raspberries and Change of Their Physical and Nutritive Properties.

Raspberries are one of Serbia's best-known and most widely exported fruits. Due to market fluctuation, producers are looking for ways to preserve this fresh product. Drying is a widely accepted method for preserving berries, as is the case with freeze-drying. Hence, the aim was to evaluate convective drying as an alternative to freeze-drying due to better accessibility, simplicity, and cost-effectiveness of Polana raspberries and compare it to a freeze-drying. Three factors were in experimental design: air temperature (60, 70, and 80 °C), air velocity (0,5 and 1,5 m · s-1), and state of a product (fresh and frozen). Success of drying was evaluated with several quality criteria: shrinkage (change of volume), color change, shape, content of L-ascorbic acid, total phenolic content, flavonoid content, anthocyanin content, and antioxidant activity. A considerable influence of convective drying on color changes was not observed, as ΔE was low for all samples. It was obvious that fresh raspberries had less physical changes than frozen ones. On average, convective drying reduced L-ascorbic acid content by 80.00-99.99%, but less than 60% for other biologically active compounds as compared to fresh raspberries. Convective dried Polana raspberry may be considered as a viable replacement for freeze-dried raspberries.

Infrared camera on a butterfly's wing.

Thermal cameras were constructed long ago, but working principles and complex technologies still limit their resolution, total number of pixels, and sensitivity. We address the problem of finding a new sensing mechanism surpassing existing limits of thermal radiation detection. Here we reveal the new mechanism on the butterfly wing, whose wing-scales act as pixels of an imaging array on a thermal detector. We observed that the tiniest features of a Morpho butterfly wing-scale match the mean free path of air molecules at atmospheric pressure - a condition when the radiation-induced heating produces an additional, thermophoretic force that deforms the wing-scales. The resulting deformation field was imaged holographically with mK temperature sensitivity and 200 Hz response speed. By imitating butterfly wing-scales, the effect can be further amplified through a suitable choice of material, working pressure, sensor design, and detection method. The technique is universally applicable to any nano-patterned, micro-scale system in other spectral ranges, such as UV and terahertz.

An Embedded Sensor Node Microcontroller with Crypto-Processors.

Wireless sensor network applications range from industrial automation and control, agricultural and environmental protection, to surveillance and medicine. In most applications, data are highly sensitive and must be protected from any type of attack and abuse. Security challenges in wireless sensor networks are mainly defined by the power and computing resources of sensor devices, memory size, quality of radio channels and susceptibility to physical capture. In this article, an embedded sensor node microcontroller designed to support sensor network applications with severe security demands is presented. It features a low power 16-bitprocessor core supported by a number of hardware accelerators designed to perform complex operations required by advanced crypto algorithms. The microcontroller integrates an embedded Flash and an 8-channel 12-bit analog-to-digital converter making it a good solution for low-power sensor nodes. The article discusses the most important security topics in wireless sensor networks and presents the architecture of the proposed hardware solution. Furthermore, it gives details on the chip implementation, verification and hardware evaluation. Finally, the chip power dissipation and performance figures are estimated and analyzed.