A watertight electrical compartment for use in an irrigation device can include a compartment body having a chamber and a sealing section configured to mate with one or more sealing rings. A sealing cap can mate with the sealing section and/or the sealing rings to seal the chamber. A cap retainer can be advanced over at least a portion of the sealing cap. One of the compartment body and cap retainer can have internal threads to be screwed onto external threads of the other one of the compartment body and cap retainer. The cap retainer can also have a stopping feature to keep the sealing cap in its sealed position. The watertight electrical compartment can be used in a wireless flow sensor assembly, a battery operated irrigation controller, and/or a battery-operated central controller device, to provide irrigation control, and/or sensor information, without the need for AC power.

An agricultural method includes providing a positive air pressure chamber to prevent outside contaminants from entering the chamber; growing crops in a plurality of cells in the chamber, each cell having multi-grow benches or levels, each cell further having connectors to vertical hoists for vertical movements in the chamber; maintaining pre-set temperature, humidity, carbon dioxide, watering and lighting levels to achieve predetermined plant growth; using motorized transport rails to deliver benches for operations including seeding, harvesting, grow media recovery, and bench wash; dispensing seeds in the cell with a mechanical seeder coupled to the transport rails; growing the crops with computer controlled nutrients, light and air level; and harvesting the crops and delivering the harvested crop at a selected outlet of the chamber.

A system, method and apparatus for monitoring and providing maintenance updates for irrigation filters. According to a first preferred embodiment, the present invention includes one or more load cells at one or more of the mounting feet of an in-line filter to actively measure the increased weight of the filter during irrigation operations. According to a further preferred embodiment, the weight sensor of the present invention may transmit its data to a processing unit, where the weight is compared to one or more stored weight values. Preferably, when the detected weight exceeds a threshold level, the system may trigger notices and/or remedial actions.

An irrigation system for an area receives wide-area meteorological prediction data and sensors deployed within the area collect local-area sensor data. A processor stores received data as historical wide-area meteorological prediction data and data from the sensors as historical local-area sensor data. The processor determines a relationship between the historical wide-area meteorological prediction data and the historical local-area sensor data based on the historical wide-area meteorological prediction data and the historical local-area sensor data, and calculates a prediction on a local-area parameter for a future point in time based on current wide-area meteorological prediction data, and the calculated relationship. The area is then controlled based on the prediction.

This disclosure relates generally to root zone moisture estimation for vegetation cover using remote sensing. Conventionally, it is challenging to estimate root zone soil moisture using only satellite data. Moreover, estimation of soil moisture under vegetation cover based on bare surface soil moisture and vegetation parameters is not available. The disclosed method and system facilitate estimation of an ensemble of soil moisture under vegetation cover and root zone soil moisture using process based soil water balance for spatial estimation of root zone soil moisture. The system estimates bare surface soil moisture for different soil types/textures using the baseline bare surface model and soil properties derived from satellite data and in-situ sensors. The method further provides temporal spatially distributed soil moisture inputs to an intelligent irrigation management/information system which is very important to reduce and regulate water consumption.

The present invention provides a solar power system for use with a mechanized irrigation system. According to a first preferred embodiment, the solar power system of the present includes solar panels which produce DC current which is used to power the irrigation system and to store water in an elevated storage tank. The systems of the present invention selectively use the water stored in the elevated storage tank to provide water pressure to the irrigation system. According to a further preferred embodiment, the system of the present invention preferably converts the power from the solar panels to AC current and uses AC current to power the movement of the irrigation system and other sub-systems.

A control apparatus includes: a determiner configured to determine, for each indicator of a plurality of indicators, whether an event relevant to a change in the respective indicator has occurred, the plurality of indicators relating to an environment in which crops are grown, each indicator of the plurality of indicators being detected by one or more sensors of a plurality of sensors; an identifier configured to identify, based on a result of a determination executed by the determiner, a plurality of target sensors from among the plurality of sensors, a number of the plurality of target sensors being less than a number of the plurality of sensors; and a transmission instructor configured to instruct each target sensor of the plurality of target sensors to transmit a respective detection result.

A method for optimizing plant growth in a hybrid growing environment may implement artificial intelligence to measure and alter plant biometrics. Independent variables may be altered by a control unit by manipulating various control systems within the growing environment. Dependent variables may be measured, and the response of the dependent variables may be recorded in association with the alteration to the independent variables. A historical database may store data regarding the variables and may be referenced and updated by an exemplary embodiment. The control unit may optimize one or more variables or parameters based on a targeted value or outcome. An exemplary hybrid growing environment may include one or more vertical growing phases and a horizontal phase. The phases may implement various watering systems and may be hydroponic, be a complete CEA, use a mixture of natural, artificial, and/or supplemental lighting.

Embodiments of the invention provide an automated plant probe system and method. The plant probe can include a body and a housing with a hardware module. The hardware module can include a communication module, an electronic controller, and memory. The plant probe can include a probe with a sensor module. The sensor module can including various sensors, such as a moisture sensor and/or a growing media sensor. The plant probe system can include a control system in communication with the communication module of the plant probe. The control system can receive plant data from the sensor module and use the plant data to provide plant recommendations.

One variation of a method for deploying sensors within an agricultural facility includes: accessing scan data of a set of modules deployed within the agricultural facility; extracting characteristics of plants occupying the set of modules from the scan data; selecting a first subset of target modules from the set of modules, each target module in the set of target modules containing a group of plants exhibiting characteristics representative of plants occupying modules neighboring the target module; for each target module, scheduling a robotic manipulator within the agricultural facility to remove a particular plant from a particular plant slot in the target module and load the particular plant slot with a sensor pod from a population of sensor pods deployed in the agricultural facility; and monitoring environmental conditions at target modules in the first subset of target modules based on sensor data recorded by the first population of sensor pods.