Implementation of a LoRaWAN Based Smart Agriculture Decision Support System for Optimum Crop Yield

A majority of the population of developing countries is associated with agriculture directly or indirectly. The liaison of engineering technology and Sustainable Development Goals (SDGs) can build a bridge for farmers to enhance their skills regarding advancements through future generation agriculture trends. The next-generation trends include better soil preparation, intelligent irrigation systems, advanced methods of crop nutrient inspection, smart fertilizers applications, and multi-cropping practices. This work proposes a smart Decision Support System (DSS) that acquires the input parameters based on real-time monitoring to optimize the yield that realizes sustainability by improving per hectare production and lessening water seepage wastage in agribusiness. The proposed model comprises three basic units including an intelligent sensor module, smart irrigation system and controlled fertilizer module. The system has integrated sensors, cloud employing decision support layers, and networking based DSS to recommend cautions for optimum sustainable yield. The intelligent sensors module contains a temperature and humidity sensor, NPK sensor, soil moisture sensor, soil conductivity sensor, and pH sensor to transmit the statistics to the cloud over the internet via Long Range (LoRa) using Serial Peripheral Interface (SPI) communication protocol. Moreover, an android application has been developed for real-time data monitoring according to GPS location and node information (accessed remotely). Furthermore, the DSS contemplates the accessible information from sensors, past patterns, monitoring climate trends and creating cautions required for sustainable fertilizer consumption. The presented results and comparison validate the novelty of the design as it embraces smart irrigation with smart control and smart decision-making based on accurate real-time field data. It is better than existing systems as it transmits the data over the LoRa that is an open-source communication with long-range transmission ability up to several kilometres. The sensor nodes helped in advancing the yield of crops, which resulted in achieving inclusive and sustainable economic goals.

Semi-Automatic Lab-on-PCB System for Agarose Gel Preparation and Electrophoresis for Biomedical Applications

In this paper, a prototype of a semi-automatic lab-on-PCB for agarose gel preparation and electrophoresis is developed. The dimensions of the device are 38 × 34 mm2 and it includes a conductivity sensor for detecting the TAE buffer (Tris-acetate-EDTA buffer), a microheater for increasing the solubility of the agarose, a negative temperature coefficient (NTC) thermistor for controlling the temperature, a light dependent resistor (LDR) sensor for measuring the transparency of the mixture, and two electrodes for performing the electrophoresis. The agarose preparation functions are governed by a microcontroller. The device requires a PMMA structure to define the wells of the agarose gel, and to release the electrodes from the agarose. The maximum voltage and current that the system requires are 40 V to perform the electrophoresis, and 1 A for activating the microheater. The chosen temperature for mixing is 80 ∘C, with a mixing time of 10 min. In addition, the curing time is about 30 min. This device is intended to be integrated as a part of a larger lab-on-PCB system for DNA amplification and detection. However, it can be used to migrate DNA amplified in conventional thermocyclers. Moreover, the device can be modified for preparing larger agarose gels and performing electrophoresis.

Automatic Lab on PCB System for Agarose Gel Preparation and Electrophoresis for Biomedical Applications

In this paper, a prototype of an automatic lab on PCB for agarose preparation and electrophoresis is developed. The dimensions of the device are 38×34 mm2 and includes a conductivity sensor for detecting the TAE buffer (Tris-Acetate-EDTA buffer), a microheater for mixing, a NTC thermistor for controlling the temperature, a LDR sensor for measuring the transparency of the mixture, and two electrodes for performing the electrophoresis. The agarose preparation functions are governed by a microcontroller. The device requires a PMMA structure to define the wells of the agarose gel, and to release the electrodes from the agarose. The maximum voltage and current that the system requires are 40 V to perform the electrophoresis, and 1 A for activating the microheater. The chosen temperature for mixing is 80ºC, with a mixing time of 10 min. In addition, the curing time is about 30 min. This device is intended to be integrated as a part of a larger lab on PCB system for DNA amplification and detection. However, it can be used to migrate DNA amplified in conventional thermocyclers. Moreover, the device can be modified for preparing larger agarose gels and performing electrophoresis in an automatic manner.

Hydrogen-Terminated Diamond Surface as a Gas Sensor: A Comparative Study of Its Sensitivities

A nanocrystalline diamond (NCD) layer is used as an active (sensing) part of a conductivity gas sensor. The properties of the sensor with an NCD with H-termination (response and time characteristic of resistance change) are measured by the same equipment with a similar setup and compared with commercial sensors, a conductivity sensor with a metal oxide (MOX) active material (resistance change), and an infrared pyroelectric sensor (output voltage change) in this study. The deposited layer structure is characterized and analyzed by Scanning Electron Microscopy (SEM) and Raman spectroscopy. Electrical properties (resistance change for conductivity sensors and output voltage change for the IR pyroelectric sensor) are examined for two types of gases, oxidizing (NO2) and reducing (NH3). The parameters of the tested sensors are compared and critically evaluated. Subsequently, differences in the gas sensing principles of these conductivity sensors, namely H-terminated NCD and SnO2, are described.

A Low-Cost Water Depth and Electrical Conductivity Sensor for Detecting Inputs into Urban Stormwater Networks

High-resolution data collection of the urban stormwater network is crucial for future asset management and illicit discharge detection, but often too expensive as sensors and ongoing frequent maintenance works are not affordable. We developed an integrated water depth, electrical conductivity (EC), and temperature sensor that is inexpensive (USD 25), low power, and easily implemented in urban drainage networks. Our low-cost sensor reliably measures the rate-of-change of water level without any re-calibration by comparing with industry-standard instruments such as HACH and HORIBA’s probes. To overcome the observed drift of level sensors, we developed an automated re-calibration approach, which significantly improved its accuracy. For applications like monitoring stormwater drains, such an approach will make higher-resolution sensing feasible from the budget control considerations, since the regular sensor re-calibration will no longer be required. For other applications like monitoring wetlands or wastewater networks, a manual re-calibration every two weeks is required to limit the sensor’s inaccuracies to ±10 mm. Apart from only being used as a calibrator for the level sensor, the conductivity sensor in this study adequately monitored EC between 0 and 10 mS/cm with a 17% relative uncertainty, which is sufficient for stormwater monitoring, especially for real-time detection of poor stormwater quality inputs. Overall, our proposed sensor can be rapidly and densely deployed in the urban drainage network for revolutionised high-density monitoring that cannot be achieved before with high-end loggers and sensors.

Improved Sensing Properties of Thermal Conductivity-Type CO2 Gas Sensors by Loading Multi-Walled Carbon Nanotubes Into Nano-Al2O3 Powders

Response time is the key index of on-line monitoring system. To improve the response speed of traditional bead thermal conductivity CO2 sensor, this paper proposes to use multi-walled carbon nanotubes (MWCNTs) to improve the performance of gas sensor carrier. Nano-sized γ-Al2O3/CeO2 powder was synthesized by chemical precipitation method under the action of ultrasonic wave. SEM morphology reveals a particle size of 20–50 nm. MWCNTs were hydroxylated and the solution was then prepared by adding a certain amount of dispersant under ultrasonic wave. The composite support of γ- Al2O3/CeO2/MWCNTs was prepared by wet mixing carbon nanotube solution into the above support materials. Using dynamic resistance matching and black component technology, the influence of radiation heat and environmental temperature and humidity is reduced. Results show that the designed thermal conductivity sensor has consistent response and recovery time to different concentrations of CO2, with a T90 response time of 9 s and a T90 recovery time of 13 s, which is faster compared to major commercial Carbon dioxide sensors. The average sensitivity of the sensor is 0.0075 V/10% CO2. Therefore, the high thermal conductivity and pore characteristics of carbon nanotubes can effectively improve the response speed of the thermal conductivity sensor.

Inferring saline tracer transport characteristics from time-lapse GPR experiments

<p>Monitoring and characterization of flow and transport processes in the subsurface has been a key focus of hydrogeological research for several decades. Such processes can be relevant for numerous applications, such as hydrocarbon and geothermal reservoir characterization and monitoring, risk assessment of soil contaminants, or nuclear waste disposal strategies.</p><p>Monitoring of flow and transport processes in the subsurface is often challenging, as they are usually not directly observable. Here, we present an approach to monitor saline tracer migration through a weakly fractured crystalline rock mass by means of Ground Penetrating Radar (GPR), and we evaluate the data quantitatively in terms of a flow velocity field and localized difference GPR breakthrough curves (DRBTC).</p><p>Two comparable and repeated tracer injection experiments were performed within saturated rock on the decameter scale. Time-lapse single-hole reflection data were acquired from two different boreholes during these experiments using unshielded and omnidirectional borehole antennas. The individual surveys were analyzed by difference imaging techniques, which allowed ultimately for tracer breakthrough monitoring at different locations in the subsurface. By combining the two complimentary GPR data sets, the 3D tracer velocity field could be reconstructed.</p><p>Our DRBTCs agree well with measured BTCs of the saline tracer at different electrical conductivity monitoring positions. Additionally, we were able to calculate a DRBTC for a location not previously monitored with borehole sensors. The reconstructed velocity field is in good agreement with previous studies on dye tracer data at the same research locations. Furthermore, we were able to resolve separate flow paths towards different monitoring locations, which could not be inferred from the electrical conductivity sensor data alone. The GPR data thus helped to disentangle the complex flow field through the fractured rock.</p><p>Out technique can be adapted to other use cases such as 3D monitoring of fluid migration (and thus permeability enhancement) during hydraulic stimulation and tracing fluid contaminants – e.g. for nuclear waste repository monitoring.</p>

Inventing a Robust Road-Vehicle Flood Level monitoring Device for User-defined Safe Threshold Alert on Road-Flood Disaster

Flooding impedes road utility and the frequency has increased across countries of the world owning to global climate change phenomena. Global road flood casualties have risen from 371,800 in 2015 to 842,000 in 2017 resulting to economic losses valued at approximately US$71 billion. Existing devices that offer warning signals on safe threshold during flooding are predictive in nature and based on complex technologies that are cumbersome and rather expensive thereby affecting the attractiveness to low-economy societies of developing countries. There is therefore a dare need for better inventions towards greater mitigation. This paper presents an adaptive, affordable, robust, efficient and effective road vehicle flood level monitoring device for detecting rising flood on roads above a user defined safe threshold to tackle road flood disasters. The device consists of a water sensing column, microcontroller unit, GSM module, transistors coupled to arrays of Light Emitting Diodes (LED) that connects to a buzzer through a Stable-Multivibrator circuit. The device operates on the principle of level conductivity sensor. The flood level notification device senses the rising flood level using water sensor probes that activates arrays of LEDs and warning alarm through a microcontroller on exceeding a permissible limit of about 60cm; sending short message service (SMS) to enrolled mobile phone number of meteorological agencies on road flood level reports. By this, road users are alerted of the dangerous flood level. The study therefore recommends for adoption of mandatory inclusion of this invention on roads towards averting the usual road flood hazard in countries.