Low Power Environmental Image Sensors for Remote Photogrammetry

Balde, Alpha Yaya; Bergeret, Emmanuel; Cajal, Denis; Toumazet, Jean‐Pierre

doi:10.3390/s22197617

Cited by 3 publications

(1 citation statement)

References 17 publications

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“…The cheap ESP32-CAM module (Figure 2a) is a low power consumption system ideal for remote monitoring IoT applications. The ESP32-CAM module contains a microcontroller with Bluetooth, Wi-Fi, and an SD card [44,45]. Its DIP format allows it to be easily and quickly integrated into any application, and the data obtained can be sent to any embedded device.…”

Section: Iot Fly Monitoring Systemmentioning

confidence: 99%

Mango Fruit Fly Trap Detection Using Different Wireless Communications

Hahn,

Valle,

Rendón

et al. 2023

Agronomy

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Fruit flies cause production losses in mango orchards affecting fruit quality. A National Campaign against Fruit Flies (NCFF) evaluates farm status using the fruit flies per trap per day index (FTD). Traps with attractant are installed manually within orchards in Mexico, but counting the flies trapped every week requires excessive numbers of trained personal. Electronic traps (e-traps) use sensors to monitor fruit fly population, saving labor and obtaining the real-time orchard infestation. The objective of this work was to acquire an image within a e-trap at 17:00 when an insect was detected and binarize the information in real-time to count the number of flies. Each e-trap was implemented with a polyethylene PET bottle screwed to a tap containing an ESP32-CAM camera. E-traps from several hectares of mango trees were sampled and transmitted through WSN wireless sensor networks. This original system presents a star topology network within each hectare with the long range LoRa transceiver at the central tower. It receives the fly count from five e-traps and finally transmits data to the house tower end point. Another contribution of this research was the use of a DJI mini2 for acquiring the e-trap data, and the 8-ha flight took 15 min and 35 s. This period can be reduced if the drone flies higher.

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Section: Iot Fly Monitoring Systemmentioning

confidence: 99%

Mango Fruit Fly Trap Detection Using Different Wireless Communications

Hahn,

Valle,

Rendón

et al. 2023

Agronomy

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Electric Drive with an Adaptive Controller and Wireless Communication System

et al. 2023

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In this paper, the problem of the remote control of electric drives with a complex mechanical structure is discussed. Oscillations of state variables and control precision are the main issues found in such applications. The article proposes a smart, IoT-enabled controller, which allows remote communication with a drive. To solve the problem of speed oscillations and to make the system robust to parameter uncertainty, an adaptive controller with two neural networks is designed. First, numerical tests are conducted in a Matlab/Simulink environment to examine the operation of the proposed control strategy. Afterwards, the obtained results are verified in a laboratory setup equipped with a 0.5 kW electric motor. Remote access is provided by a low-cost, ARM-based ESP32 microcontroller. Usually, virtual instruments used to communicate with remote devices require specific software, which may be expensive and pose compatibility problems. Therefore, the main contribution of the article is the creation of a low-cost, web-based Human-Machine Interface (HMI) with an asynchronous server utility provided by the ESP32 that allows remote control and data acquisition of electric drive state variables.

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Dynamic Reconstruction and Mesh Compression of 4D Volumetric Model Using Correspondence-Based Deformation for Streaming Service

Park

Lee

Park

et al. 2022

Sensors

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A sequence of 3D models generated using volumetric capture has the advantage of retaining the characteristics of dynamic objects and scenes. However, in volumetric data, since 3D mesh and texture are synthesized for every frame, the mesh of every frame has a different shape, and the brightness and color quality of the texture is various. This paper proposes an algorithm to consistently create a mesh of 4D volumetric data using dynamic reconstruction. The proposed algorithm comprises remeshing, correspondence searching, and target frame reconstruction by key frame deformation. We make non-rigid deformation possible by applying the surface deformation method of the key frame. Finally, we propose a method of compressing the target frame using the target frame reconstructed using the key frame with error rates of up to 98.88% and at least 20.39% compared to previous studies. The experimental results show the proposed method’s effectiveness by measuring the geometric error between the deformed key frame and the target frame. Further, by calculating the residual between two frames, the ratio of data transmitted is measured to show a compression performance of 18.48%.

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Low Power Environmental Image Sensors for Remote Photogrammetry

Cited by 3 publications

References 17 publications

Mango Fruit Fly Trap Detection Using Different Wireless Communications

Mango Fruit Fly Trap Detection Using Different Wireless Communications

Electric Drive with an Adaptive Controller and Wireless Communication System

Dynamic Reconstruction and Mesh Compression of 4D Volumetric Model Using Correspondence-Based Deformation for Streaming Service

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