Emerging technologies such as Internet of Things (IoT) can provide significant potential in Smart Farming and Precision Agriculture applications, enabling the acquisition of real-time environmental data. IoT devices such as Unmanned Aerial Vehicles (UAVs) can be exploited in a variety of applications related to crops management, by capturing high spatial and temporal resolution images. These technologies are expected to revolutionize agriculture, enabling decision-making in days instead of weeks, promising significant reduction in cost and increase in the yield. Such decisions enable the effective application of farm inputs, supporting the four pillars of precision agriculture, i.e., apply the right practice, at the right place, at the right time and with the right quantity. However, the actual proliferation and exploitation of UAVs in Smart Farming has not been as robust as expected mainly due to the challenges confronted when selecting and deploying the relevant technologies, including the data acquisition and image processing methods. The main problem is that still there is no standardized workflow for the use of UAVs in such applications, as it is a relatively new area. In this article, we review the most recent applications of UAVs for Precision Agriculture. We discuss the most common applications, the types of UAVs exploited and then we focus on the data acquisition methods and technologies, appointing the benefits and drawbacks of each one. We also point out the most popular processing methods of aerial imagery and discuss the outcomes of each method and the potential applications of each one in the farming operations.

https://www.mdpi.com/2078-2489/10/11/349/pdf

A Review on UAV-Based Applications for Precision Agriculture

Preface. About the Authors. Acknowledgments. 1 Power Amplifier Fundamentals. 1.1 Introduction. 1.2 Definition of Power Amplifier Parameters. 1.3 Distortion Parameters. 1.4 Power Match Condition. 1.5 Class of Operation. 1.6 Overview of Semiconductors for PAs. 1.7 Devices for PA. 1.8 Appendix: Demonstration of Useful Relationships. 1.9 References. 2 Power Amplifier Design. 2.1 Introduction. 2.2 Design Flow. 2.3 Simplified Approaches. 2.4 The Tuned Load Amplifier. 2.5 Sample Design of a Tuned Load PA. 2.6 References. 3 Nonlinear Analysis for Power Amplifiers. 3.1 Introduction. 3.2 Linear vs. Nonlinear Circuits. 3.3 Time Domain Integration. 3.4 Example. 3.5 Solution by Series Expansion. 3.6 The Volterra Series. 3.7 The Fourier Series. 3.8 The Harmonic Balance. 3.9 Envelope Analysis. 3.10 Spectral Balance. 3.11 Large Signal Stability Issue. 3.12 References. 4 Load Pull. 4.1 Introduction. 4.2 Passive Source/Load Pull Measurement Systems. 4.3 Active Source/Load Pull Measurement Systems. 4.4 Measurement Test-sets. 4.5 Advanced Load Pull Measurements. 4.6 Source/Load Pull Characterization. 4.7 Determination of Optimum Load Condition. 4.8 Appendix: Construction of Simplified Load Pull Contours through Linear Simulations. 4.9 References. 5 High Efficiency PA Design Theory. 5.1 Introduction. 5.2 Power Balance in a PA. 5.3 Ideal Approaches. 5.4 High Frequency Harmonic Tuning Approaches. 5.5 High Frequency Third Harmonic Tuned (Class F). 5.6 High Frequency Second Harmonic Tuned. 5.7 High Frequency Second and Third Harmonic Tuned. 5.8 Design by Harmonic Tuning. 5.9 Final Remarks. 5.10 References. 6 Switched Amplifiers. 6.1 Introduction. 6.2 The Ideal Class E Amplifier. 6.3 Class E Behavioural Analysis. 6.4 Low Frequency Class E Amplifier Design. 6.5 Class E Amplifier Design with 50# Duty-cycle. 6.6 Examples of High Frequency Class E Amplifiers. 6.7 Class E vs. Harmonic Tuned. 6.8 Class E Final Remarks. 6.9 Appendix: Demonstration of Useful Relationships. 6.10 References. 7 High Frequency Class F Power Amplifiers. 7.1 Introduction. 7.2 Class F Description Based on Voltage Wave-shaping. 7.3 High Frequency Class F Amplifiers. 7.4 Bias Level Selection. 7.5 Class F Output Matching Network Design. 7.6 Class F Design Examples. 7.7 References. 8 High Frequency Harmonic Tuned Power Amplifiers. 8.1 Introduction. 8.2 Theory of Harmonic Tuned PA Design. 8.3 Input Device Nonlinear Phenomena: Theoretical Analysis. 8.4 Input Device Nonlinear Phenomena: Experimental Results. 8.5 Output Device Nonlinear Phenomena. 8.6 Design of a Second HT Power Amplifier. 8.7 Design of a Second and Third HT Power Amplifier. 8.8 Example of 2nd HT GaN PA. 8.9 Final Remarks. 8.10 References. 9 High Linearity in Efficient Power Amplifiers. 9.1 Introduction. 9.2 Systems Classification. 9.3 Linearity Issue. 9.4 Bias Point Influence on IMD. 9.5 Harmonic Loading Effects on IMD. 9.6 Appendix: Volterra Analysis Example. 9.7 References. 10 Power Combining. 10.1 Introduction. 10.2 Device Scaling Properties. 10.3 Power Budget. 10.4 Power Combiner Classification. 10.5 The T-junction Power Divider. 10.6 Wilkinson Combiner. 10.7 The Quadrature (90 ) Hybrid. 10.8 The 180 Hybrid (Ring Coupler or Rat-race). 10.9 Bus-bar Combiner. 10.10 Other Planar Combiners. 10.11 Corporate Combiners. 10.12 Resonating Planar Combiners. 10.13 Graceful Degradation. 10.14 Matching Properties of Combined PAs. 10.15 Unbalance Issue in Hybrid Combiners. 10.16 Appendix: Basic Properties of Three-port Networks. 10.17 References. 11 The Doherty Power Amplifier. 11.1 Introduction. 11.2 Doherty's Idea. 11.3 The Classical Doherty Configuration. 11.4 The 'AB-C' Doherty Amplifier Analysis. 11.5 Power Splitter Sizing. 11.6 Evaluation of the Gain in a Doherty Amplifier. 11.7 Design Example. 11.8 Advanced Solutions. 11.9 References. Index.

/pdf/high-efficiency-rf-and-microwave-solid-state-power-4xdx1261hq.pdf

High Efficiency RF and Microwave Solid State Power Amplifiers

Soybean yield prediction from UAV using multimodal data fusion and deep learning

This expanded and thoroughly revised edition of Thomas H. Lee's acclaimed guide to the design of gigahertz RF integrated circuits features a completely new chapter on the principles of wireless systems. The chapters on low-noise amplifiers, oscillators and phase noise have been significantly expanded as well. The chapter on architectures now contains several examples of complete chip designs that bring together all the various theoretical and practical elements involved in producing a prototype chip. First Edition Hb (1998): 0-521-63061-4 First Edition Pb (1998); 0-521-63922-0

The Design of CMOS Radio-Frequency Integrated Circuits: RF CIRCUITS THROUGH THE AGES

Internet of Things in arable farming: Implementation, applications, challenges and potential

A low power 60-GHz on-off-keying (OOK) receiver has been implemented in a commercial 90 nm RF CMOS process. By employing a novel on-chip antenna together with architecture optimization, the receiver achieves a sensitivity of 47 dBm at a bit-error rate (BER) of less than 10 . Using a commercial trans- mitterwithtransmitpowerof1.5dBm,atransmissiondistanceof5 cmcanbeachievedat1.2Gbpsdatarate.Inthisdesign,theon-chip antenna minimizes the packaging loss, while energy detection at RF allows architecture simplification. Both techniques contribute to the receiver's low power consumption of 51 mW, excluding test buffers. This leads to abit energyefficiency of 28 pj/bit at 1.8 Gbps. The total die area is 3.8 mm with the on-chip antenna occupying almost half of it.

A 60-GHz OOK Receiver With an On-Chip Antenna

The intermodulation performance of an FET in the common-source configuration is dependent on the impedance presented to its gate and drain terminals, not only at fundamental, but also at harmonic and baseband frequencies. At baseband frequencies, these terminating impedances are usually determined by the bias networks, which may have varying impedance over the frequencies involved. This can give rise to asymmetry in two-tone intermodulation levels, and changing intermodulation levels with tone spacing, as previous studies have shown. In this paper, an FET is analyzed to gain an understanding, useful to the circuit designer, of the contributing mechanisms, and to enable the prediction of bias points and the design of networks that can minimize or maximize these effects. Compact formulas are given to facilitate this. An amplifier was tested, showing good agreement between the theoretical and measured results.

Effect of baseband impedance on FET intermodulation

A low power 60-GHz on-off-keying (OOK) receiver has been implemented in a commercial 90 nm RF CMOS process. By employing a novel on-chip antenna together with architecture optimization, the receiver achieves a sensitivity of -47 dBm at a bit-error rate (BER) of less than 10-3. Using a commercial transmitter with transmit power of 1.5 dBm, a transmission distance of 5 cm can be achieved at 1.2 Gbps data rate. In this design, the on-chip antenna minimizes the packaging loss, while energy detection at RF allows architecture simplification. Both techniques contribute to the receiver's low power consumption of 51 mW, excluding test buffers. This leads to a bit energy efficiency of 28 pj/bit at 1.8 Gbps. The total die area is 3.8 mm2 with the on-chip antenna occupying almost half of it.

A 60-GHz OOK Receiver With an On-Chip Antenna in 90 nm CMOS

A new equivalent-circuit model for transmission lines and inductors on silicon is proposed. The SPICE-compatible model is suitable for time-domain simulators. It is able to fit the frequency-dependent behavior of the RLGC parameters well into the millimeter-wave range. The model is extracted from electromagnetic simulations with a simple analytic procedure with no need for tuning or optimization. A method for making the model scalable with both line length and width (or inductor diameter) is proposed. Based on this new model, a scalable measurement deembedding methodology is proposed, that can greatly reduce wafer area needed for test and deembedding structures. The fully scalable model results are compared with measurements of devices fabricated in a 90 nm CMOS process.

Scalable Transmission Line and Inductor Models for CMOS Millimeter-Wave Design

The present work assessed the usefulness of a set of spectral indices obtained from an unmanned aerial system (UAS) for tracking spatial and temporal variability of nitrogen (N) status as well as for predicting lint yield in a commercial cotton (Gossypium hirsutum L.) farm. Organic, inorganic and a combination of both types of fertilizers were used to provide a range of eight N rates from 0 to 340 kg N ha−1. Multi-spectral images (reflectance in the blue, green, red, red edge and near infrared bands) were acquired on seven days throughout the season, from 62 to 169 days after sowing (DAS), and data were used to compute structure- and chlorophyll-sensitive vegetation indices (VIs). Above-ground plant biomass was sampled at first flower, first cracked boll and maturity and total plant N concentration (N%) and N uptake determined. Lint yield was determined at harvest and the relationships with the VIs explored. Results showed that differences in plant N% and N uptake between treatments increased as the season progressed. Early in the season, when fertilizer applications can still have an effect on lint yield, the simplified canopy chlorophyll content index (SCCCI) was the index that best explained the variation in N uptake and plant N% between treatments. Around first cracked boll and maturity, the linear regression obtained for the relationships between the VIs and both plant N% and N uptake was statistically significant, with the highest r2 values obtained at maturity. The normalized difference red edge (NDRE) index, and SCCCI were generally the indices that best distinguished the treatments according to the N uptake and total plant N%. Treatments with the highest N rates (from 307 to 340 kg N ha−1) had lower normalized difference vegetation index (NDVI) than treatments with 0 and 130 kg N ha−1 at the first measurement day (62 DAS), suggesting that factors other than fertilization N rate affected plant growth at this early stage of the crop. This fact affected the earliest date at which the structure-sensitive indices NDVI and the visible atmospherically resistant index (VARI) enabled yield prediction (97 DAS). A statistically significant linear regression was obtained for the relationships between SCCCI and NDRE with lint yield at 83 DAS. Overall, this study shows the practicality of using an UAS to monitor the spatial and temporal variability of cotton N status in commercial farms. It also illustrates the challenges of using multi-spectral information for fertilization recommendation in cotton at early stages of the crop.

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James Brinkhoff

Papers

A 60-GHz OOK Receiver With an On-Chip Antenna

Effect of baseband impedance on FET intermodulation

A 60-GHz OOK Receiver With an On-Chip Antenna in 90 nm CMOS

Scalable Transmission Line and Inductor Models for CMOS Millimeter-Wave Design

Assessment of in-season cotton nitrogen status and lint yield prediction from unmanned aerial system imagery