A moisture sensor is configured to be deployed in soil for measuring a moisture content. The moisture sensor includes a housing; a transistor configured to interact with water from the soil; a power source configured to generate an electrical current; and a processing unit configured to receive a reading from the transistor, and to calculate the moisture content of the soil based on the reading. The transistor includes a metal-organic framework, MOF.

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.

Implementations are disclosed for adaptively reallocating computing resources of resource-constrained devices between tasks performed in situ by those resource-constrained devices. In various implementations, while the resource-constrained device is transported through an agricultural area, computing resource usage of the resource-constrained device ma may be monitored. Additionally, phenotypic output generated by one or more phenotypic tasks performed onboard the resource-constrained device may be monitored. Based on the monitored computing resource usage and the monitored phenotypic output, a state may be generated and processed based on a policy model to generate a probability distribution over a plurality of candidate reallocation actions. Based on the probability distribution, candidate reallocation action(s) may be selected and performed to reallocate at least some computing resources between a first phenotypic task of the one or more phenotypic tasks and a different task while the resource-constrained device is transported through the agricultural area.

A data collection device includes a main control module, at least one sensing module and a battery module. The main control module has at least one first connecting portion and at least one second connecting portion. The at least one sensing module is connected to the main control module. The at least one sensing module has a first conducting portion, an insulating layer and a second conducting portion. The insulating layer surrounds the first conducting portion. The second conducting portion surrounds the insulating layer. A top of the first conducting portion forms a first contacting portion. A bottom of the first conducting portion protrudes downward to form a second contacting portion. The first contacting portion is connected to the at least one first connecting portion. A top of the second conducting portion is connected to the at least one second connecting portion.

The invention relates to the field of soil analysis, in particular the technical analysis of agricultural or horticultural soils. In particular, the invention relates to a sensor device for in situ soil analysis, to a method for in situ soil analysis, and to a device set up for carrying out the soil analysis method, wherein said device, together and in interaction with one or more of said sensor devices, represents a system for in situ soil analysis. The sensor device has a sensor assembly comprising one or more sensors which are configured individually or cumulatively for the simultaneous in situ measurement of at least two of the following soil properties of a soil to be analyzed and for providing corresponding respective measurement data: (a) impedance spectrum, (b) temperature, (c) absorption spectrum NIR-VIS-UV in a spectral range from NIR (near infrared spectral range) to UV (ultraviolet spectral range), and (d) acidic or basic character, in particular pH value. In this case, the distance between in each case two of the sensors of the sensor assembly, which is defined with respect to the respective measurement variable sensors, does not exceed a value of 10 cm.

A system for detecting fungus, virus, and disease-causing pathogens in an agricultural industry using artificial intelligence, which comprises: an unmanned aerial vehicle (UAV); and a ground terminal telecommunicating with the UAV using a wireless access communication, wherein the UAV comprises a wireless transmitter for transmitting data to and from the ground terminal, an array of cantilevers on a substrate located at one side of the wireless transmitter, a blacklight located at the other side of the wireless transmitter, and a sensory part located on the wireless transmitter, wherein the cantilever is made up of beams anchored at one end and projecting into space, and wherein the sensory part comprises a scanner with a high-definition microscope camera, a laser sensor for three-dimensional areal mapping, an infrared sensor, a humidity sensor, a thermostat, a gas sensor, a thermal sensor, an optical dust particle sensor, an electro-optical sensor, and an air quality sensor, and wherein the ground terminal comprises an artificial intelligence machine-learning and data-mining platform wirelessly telecommunicating with the UAV.

A soil modeling and mapping framework for use in precision agriculture analyzes remotely-sensed data pertaining to characteristics of one or more agricultural fields, and determines optimal sampling locations from information in remotely-sensed information, terrain derivatives and satellite imagery, to develop a customized sampling design for modeling soil properties in such agricultural fields that optimized for the particular landscape in such fields. The soil modeling and mapping framework then analyzes soil samples collected based on the customized sampling design in machine learning-based models that predict soil properties in sampled, semi-sampled, and unsampled target fields. The predicted soil properties are used to develop highly-accurate maps of soil properties such as fertility maps, which may further be used for defining and creating one or more management zones with recommendations for applying the right amount of nutrients at variable rates in the correct areas.

Speed control of machines and associated implements during transitions of agricultural parameters is described herein. In one embodiment, a processing system comprises processing logic to execute instructions for processing agricultural data and performing speed control of a machine and associated implement during a transition period for adjusting a setting of an agricultural parameter. A communication unit is coupled to the processing logic. The communication unit to transmit and receive data from the implement. The processing logic is configured to execute instructions to adjust the setting of the agricultural parameter and to determine a desired speed control during the transition period based on at least one of a desired transition distance and productivity during the transition period.

A soil apparatus is drawn through a furrow and reflectance from the furrow is obtained from the soil apparatus, and a height off target is measured between the soil apparatus and the furrow.

A soil sampler attachable to a vehicle for agricultural uses includes a collector configured to collect a soil sample from a field as the vehicle advances across the field. The soil sampler further includes a preprocessor connected to the collector and configured to receive the soil sample from the collector and to preprocess the soil sample to dilute the soil sample. The soil sampler also includes a sensor connected to the preprocessor and configured to determine a concentration of at least one analyte in the soil sample. The soil sampler further includes a disposer connected to the sensor and configured to dispose the soil sample after the sensor determines the concentration of the at least one analyte in the soil sample.