Automated positioning dual-axis solar tracking system with precision elevation and azimuth angle control

Soil sensors and plant wearables play a critical role in smart and precision agriculture via monitoring real-time physical and chemical signals in the soil, such as temperature, moisture, pH, and pollutants and providing key information to optimize crop growth circumstances, fight against biotic and abiotic stresses, and enhance crop yields Herein, the recent advances of the important soil sensors in agricultural applications, including temperature sensors, moisture sensors, organic matter compounds sensors, pH sensors, insect/pest sensors, and soil pollutant sensors are reviewed Major sensing technologies, designs, performance, and pros and cons of each sensor category are highlighted Emerging technologies such as plant wearables and wireless sensor networks are also discussed in terms of their applications in precision agriculture The research directions and challenges of soil sensors and intelligent agriculture are finally presented

Soil Sensors and Plant Wearables for Smart and Precision Agriculture.

http://www.scielo.org.mx/pdf/jart/v15n2/2448-6736-jart-15-02-132.pdf

Room-temperature ferromagnetism in Ni-doped TiO2 diluted magnetic semiconductor thin films

Merging Biology and Solid‐State Lighting: Recent Advances in Light‐Emitting Diodes Based on Biological Materials

A low-cost (6 Euro per sensor), low-power (in the order of $200~\mu \text{W}$ per sensor), with high communication range (on the order of 250 m), scatter radio sensor network is presented, for soil moisture monitoring at multiple locations. The proposed network utilizes analog frequency modulation in a bistatic network architecture (i.e., the emitter and reader are not colocated), while the sensors operate simultaneously, using frequency-division multiple access. In contrast to prior art, this paper utilizes an ultralow-cost software-defined radio reader and offers custom microstrip capacitive sensing with simple calibration, as well as modulation pulses for each scatter radio sensor with 50% duty cycle; the latter is necessary for scalable network designs. The overall root mean squared error below 1% is observed, even for the range of 250 m. This is another small (but concrete) step for the adoption of scatter radio technology as a key enabling technology for scalable, large-scale, low-power, and cost environmental sensor networking.

/pdf/soil-moisture-scatter-radio-networking-with-low-power-2920sx7hwc.pdf

Soil Moisture Scatter Radio Networking With Low Power

The renewable-energy sector is fast gaining ground as a new growth area for numerous countries with the vast potential it presents environmentally and economically. Solar energy plays an important role as a primary source of energy, especially for rural area. This paper presents the design and development of high-efficiency dual-axis solar tracking system using Arduino platform. Furthermore, the ultimate objective of this project is to trace the maximum sunlight source to power the solar panel. The project is divided into two stages, which are hardware and software development. In hardware development, five light dependent resistor (LDR) has been used for capturing maximum light source. Two servo motors have been used to move the solar panel at maximum light source location sensing by LDR. Moreover, the code is constructed using C programming language and targeted to Arduino UNO controller. The efficiency of the system has been tested and compared with static solar panel on several time intervals, and it shows the system react the best at the 10-minutes intervals with consistent voltage generated. Therefore, the system has been proven working for capturing the maximum sunlight source for high efficiency solar harvesting applications.

High-efficiency dual-axis solar tracking developement using Arduino

To predict the negative bias temperature instability (NBTI) toward the end of pMOSFETs’ ten years lifetime, power-law-based extrapolation is the industrial standard method. The prediction accuracy crucially depends on the accuracy of time exponents, n. n reported by early work spreads in a wide range and varies with measurement conditions, which can lead to unacceptable errors when extrapolated to ten years. The objective of this paper is to find how to make n extraction independent of measurement conditions. After removing the contribution from as-grown hole traps, a new method is proposed to capture the generated defects (GDs) in their entirety. n extracted by this method is around 0.2 and insensitive to measurement conditions for the four fabrication processes we tested. The model based on this method is verified by comparing its prediction with measurements. Under ac operation, the model predicts that the GD can contribute to ~90% of NBTI at ten years.

/pdf/reliable-time-exponents-for-long-term-prediction-of-negative-2q7genj2tq.pdf

Reliable Time Exponents for Long Term Prediction of Negative Bias Temperature Instability by Extrapolation

In this study, a fringing electric field (FEF)- capacitance based wireless soil moisture sensor has been designed, fabricated and tested to measure the volumetric water content (VWC) of soil for application in precision agriculture. Typically, the performance of the sensor is evaluated based on parameters such as penetration depth, signal strength, sensitivity and linear response. This paper presents the simulation results for the sensitivity analysis of the soil moisture sensor due to the effects of the electrode size and number of ground electrode. Simulations are conducted using finite element analysis (FEA) software, Finite Element Method Magnetics® (FEMM). From the simulation results, selected design of the FEF soil moisture sensors have been fabricated using printed circuit board technology. During testing, the measured capacitance from the sensor is connected directly to the device input using capacitance to digital converter. Data obtained from the sensor will be transferred wirelessly to the Zigbee coordinator; which is connected to the data base; using sensor mote. Testing revealed that the sensor is capable of detecting moisture from 1% to 80% VWC with a linear response. Test results obtained are then compared with FEMM simulations and benchmark sensor for validation purpose.

Design, Fabrication and Testing of Fringing Electric Field Soil Moisture Sensor for Wireless Precision Agriculture Applications

Negative bias temperature instability (NBTI)-generated defects (GDs) have been widely observed and known to play an important role in device’s lifetime. However, its characterization and modeling in nanoscaled devices is a challenge due to their stochastic nature. The objective of this paper is to develop a fast and accurate technique for characterizing the statistical properties of NBTI aging, which can be completed in one day and thus reduce test time significantly. The fast speed comes from replacing the conventional constant voltage stress by the voltage step stress (VSS), while the accuracy comes from capturing the GDs without recovery. The key advances are twofold: first, we demonstrate that this VSS-GD technique is applicable for nanoscaled devices; second, we verify the accuracy of the statistical model based on the parameters extracted from this technique against independently measured data. The proposed method provides an effective solution for GD evaluation, as required when qualifying a CMOS process.

/pdf/nbti-generated-defects-in-nanoscaled-devices-fast-5gnz808g9i.pdf

NBTI-Generated Defects in Nanoscaled Devices: Fast Characterization Methodology and Modeling

As CMOS scales down, hot carrier aging (HCA) scales up and can be a limiting aging process again. This has motivated re-visiting HCA, but recent works have focused on accelerated HCA by raising stress biases and there is little information on HCA under use-biases. Early works proposed that HCA mechanism under high and low biases are different, questioning if the high-bias data can be used for predicting HCA under use-bias. A key advance of this work is proposing a new methodology for evaluating the HCA-induced variation under use-bias. For the first time, the capability of predicting HCA under use-bias is experimentally verified. The importance of separating RTN from HCA is demonstrated. We point out the HCA measured by the commercial Source-Measure-Unit (SMU) gives erroneous power exponent. The proposed methodology minimizes the number of tests and the model requires only 3 fitting parameters, making it readily implementable.

/pdf/hot-carrier-aging-and-its-variation-under-use-bias-kinetics-4qll7ejs71.pdf

Azrif Manut

Papers

High-efficiency dual-axis solar tracking developement using Arduino

Reliable Time Exponents for Long Term Prediction of Negative Bias Temperature Instability by Extrapolation

Design, Fabrication and Testing of Fringing Electric Field Soil Moisture Sensor for Wireless Precision Agriculture Applications

NBTI-Generated Defects in Nanoscaled Devices: Fast Characterization Methodology and Modeling

Hot carrier aging and its variation under use-bias: Kinetics, prediction, impact on Vdd and SRAM