A Communication Framework for Image Transmission through LPWAN Technology
Abstract
:1. Introduction
2. Related Work
3. Proposed Framework
3.1. Stage I: Processing and Classification
3.2. Stage II: Compressive Sensing
3.3. Stage III: Transmission Bandwidth Increase
3.4. Stage IV: Postprocessing and Reconstruction
3.5. Framework Interconnection
3.5.1. LoRa PHY Modulation
3.5.2. Stage Flow Process
4. Analysis Results
5. Discussion
6. Conclusions
- Finding a way to capture the image directly in the crop is required because the image is placed on a neutral background in the manner given in this article. There are several conditions that must be met while taking a photograph in an uncontrolled environment, such as brightness, shades, angle of incidence of the sun, and more. These factors have an impact on the real image and can lead to representation and classification problems.
- Integrate a complete system capable of taking an image, compressing it, transmitting and receiving, reconstructing the information, and finally displaying it. As a result, the phases must be integrated into the proposed framework, which executes the processes through an autonomous system that performs all of the processes independently.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
IoT | Internet of Things |
LPWAN | Low-Power Wide-Area Networks |
CS | Compressive Sensing |
LTE-M | Long-Term Evolution Machine |
NB-IoT | Narrow Band-IoT |
ISM | Industrial, Scientific, and Medical |
SF | Spreading Factor |
BW | Bandwidth |
ToA | Time over the Air |
SDR | Software-Defined Radio |
PSNR | Peak Signal-to-Noise Ratio |
CSMA | Carrier Sense Multiple Access |
IHT | Iterative Hard Thresholding |
OMP | Orthogonal Matching Pursuit |
GPSR | Gradient Projection for Sparse Reconstruction |
Twist | Two-Step Iterative Shrinkage/Thresholding |
MIMO | Multiple In Multiple Out |
SIMO | Single In Multiple Out |
MSE | Mean Squared Error |
FFT | Fast Fourier Transform |
Appendix A
- N: Information vector.
- n: Rows/columns of matrix.
- s: Signal.
- S: Vector.
- R: Image dimension.
- k: Dispersion relation.
- f: Linear transformation.
- M: Sampled information.
- S: Resolution vector.
- MSE: Mean Squared Error.
- m,n: Lenght nd width of image.
- I: Intensity of pixels in transmitter node.
- K: Intensity of pixels in receiver node.
- Scss: Chirp spread spectrum signal.
- t: Period.
- BW: Bandwidth.
- : Symbol time.
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Reference | Method | Transmission Time (One Image) (Min) | Packets Number | Image Compression Method |
---|---|---|---|---|
Pham, 2016 [73] | Image compression Discrete Cosine Transform | - | 8–10 | JPEG |
Kirichek et al., 2017 [78] | Fragmentation data | 6 | 700 | JPEG/JPEG2000 |
Jebril et al., 2018 [15] | Data encrypted hexadecimal | 1.1 | 314 | JPEG |
Pham, 2018 [18] | CSMA (avoid collisions) | - | 5 | JPEG |
Fan and Ding, 2018 [16] | Multiple out single in | - | - | - |
Chen et al., 2019 [79] | MPLR protocol Tx/Rx | 0.3 | - | - |
Ji et al., 2019 [76] | Image processing (Only transmits data with change) | - | - | - |
Wei et al., 2020 [80] | 1 | 85 | JPEG | |
Juliando et al., 2021 [81] | - | 858 | - | - |
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Chaparro B., F.; Pérez, M.; Mendez, D. A Communication Framework for Image Transmission through LPWAN Technology. Electronics 2022, 11, 1764. https://doi.org/10.3390/electronics11111764
Chaparro B. F, Pérez M, Mendez D. A Communication Framework for Image Transmission through LPWAN Technology. Electronics. 2022; 11(11):1764. https://doi.org/10.3390/electronics11111764
Chicago/Turabian StyleChaparro B., Fabián, Manuel Pérez, and Diego Mendez. 2022. "A Communication Framework for Image Transmission through LPWAN Technology" Electronics 11, no. 11: 1764. https://doi.org/10.3390/electronics11111764