Disclosed are various embodiments for optimized sensor deployment and fault detection in the context of agricultural irrigation and similar applications. For instance, a computing device may execute a genetic algorithm (GA) routine to determine an optimal sensor deployment scheme such that a mean-time-to-failure (MTTF) for the system is maximized, thereby improving communication of sensor measurements. Moreover, in various embodiments, a centralized fault detection scheme may be employed and a soil moisture of a field can be determined by statistically inferring soil moistures at locations of faulty nodes using spatial and temporal correlations.

Soil moisture monitoring systems and methods for measuring mutual inductance of area of influence using radio frequency stimulus are disclosed herein. An example device includes a master element stacked vertically on top of one or more slave elements. The master element and slave elements can communicate through a 1-wire bus configuration. The master element can determine the presence and location of each of the one or more slave elements using an auto-discovery process. The master element can issue commands to the one or more slave elements to obtain moisture readings and/or temperature readings.

A compost monitoring device for use in monitoring properties of a body of compost, the compost monitoring device being configured to be positioned proximate to the body of compost in use, and including: a sensor array including sensors for sensing properties of gas proximate to the body of compost, the sensors including a temperature sensor for sensing a temperature of the gas, a humidity sensor for sensing a relative humidity of the gas, and a gas sensor for detecting a level of a gas compound emitted from the compost within the gas; a wireless transceiver for wirelessly communicating with another device located remotely from the body of compost; and a controller configured to obtain sensor data from the sensors; generate monitoring data using at least some of the sensor data, and cause the monitoring data to be transmitted to the other device using the wireless transceiver.

A soil apparatus (e.g., a knife) to engage in soil is described herein. In one embodiment, the soil apparatus includes a soil engaging portion to engage with soil and a plurality of sensors disposed in the soil apparatus. Each sensor is independently pivotable to independently position for sensing soil characteristics of soil.

In order to achieve a more effective application of a crop efficiency product, a computer-implemented method is provided for applying a crop efficiency product to at least one crop in a field. The method comprises the steps of collecting remotely-sensed data of the field before an application of the crop efficiency product in the field, determining, based on the collected remotely-sensed data, at least one soil parameter at a plurality of locations in the field, generating, for each of the plurality of locations, a predicted yield response to the application of the crop efficiency product for the at least one crop based on the at least one determined soil parameter and a prediction model, wherein the prediction model is parametrized or trained based on a sample set including a plurality of different values of the at least one soil parameter and associated yield responses for the at least one crop under the application of the crop efficiency product, deciding, for each of the plurality of locations in the field, whether to treat or not based on the predicted yield response, and outputting information indicative of the decision useable to activate at least one treatment device to comply with the decision.

A system for collecting and chemically analyzing water samples extracted from the soil to measure one or more analytes of interest such as soil nutrient levels of agricultural interest for increasing crop yield and quality in one use of the system. The system includes a sample collection probe (20) comprising a filter media (26) arranged to contact the soil when embedded therein and capture a water sample from the soil, and operably coupled to a sample processing sub-system (180) thereby collectively forming a sampling station (190). The sub-system (180) is configured to receive and analyze the water sample. A programmable probe controller (60) directs operation of the sample collection, processing, and chemical analysis in situ. A networked array (110) of sampling probes dispersed throughout the field may communicate wirelessly with at least one remote electronic device such as via the cloud computing (102). A modular version of a sampling probe (200) permits customized sampling at various soil depths.

The present invention is a sensor device comprising: a housing; a processing unit assembly disposed within the housing, wherein the processing unit comprising a high frequency oscillator, a first voltage meter, a low frequency oscillator, a second voltage meter; a probe having a predetermined shape and profile attached to the processing unit and extending from the housing a predetermined distance; and a first sensing unit integrated into the probe and in electrical communication with the high frequency oscillator and the first voltage meter; a second sensing unit integrated into the probe relative to the first sensing unit and in electrical communication with the low frequency oscillator and the second voltage meter.

The present disclosure provides a method for detection of soil heavy metal pollution using an unmanned aerial vehicle (UAV) and an X-ray fluorescence (XRF) technology. Based. Based on hardware equipment such as the UAV, XRF analyzer, and embedded equipment, the present disclosure develops an altitude hold module of the system and a ground-contact monitoring module, and assists the UAV to achieve safe and accurate fixed-point hovering, and develops a driving device for data acquisition to replace manual control and realize the automatic acquisition of XRF data. The data inversion method is realized by using embedded equipment, and after the data is acquired by the portable XRF analyzer near the ground, the algorithm research of inversion processing of contents of heavy metal elements in soil is realized, such that the portable XRF analyzer can automatically and accurately detect the contents of heavy metals in soil at a certain distance.

A pH measurement system includes a measurement apparatus that is capable of connection to a mobile device and a server and that includes a measuring instrument and a monitoring device. The measuring instrument includes a tube, and a sensor rod that is disposed is the tube and that is for sensing a pH value of a measurement target. The monitoring device includes a microcontroller communicatively connected to the sensor rod, an operation module for operation by a user, a communication module for communication with the mobile device and the server, and a display module for displaying information. The microcontroller provides the pH value to the mobile device or the server through the communication module.

Disclosed are various embodiments for optimized sensor deployment and fault detection in the context of agricultural irrigation and similar applications. For instance, a computing device may execute a genetic algorithm (GA) routine to determine an optimal sensor deployment scheme such that a mean-time-to-failure (MTTF) for the system is maximized, thereby improving communication of sensor measurements. Moreover, in various embodiments, a centralized fault detection scheme may be employed and a soil moisture of a field can be determined by statistically inferring soil moistures at locations of faulty nodes using spatial and temporal correlations.