WO2010125236A1

WO2010125236A1 - Method and apparatus of collecting data for agricultural analysis

Info

Publication number: WO2010125236A1
Application number: PCT/FI2010/050317
Authority: WO
Inventors: Jan Otto Blom; Dhaval Joshi; Vijay Narayanan-Saroja
Original assignee: Nokia Corporation
Priority date: 2009-05-01
Filing date: 2010-04-20
Publication date: 2010-11-04
Also published as: BRPI1010018A2; CN102414713A

Abstract

An approach is provided for analyzing agricultural information using a mobile device. Data about an agricultural product using a mobile device is collected. Location information corresponding to the agricultural product is acquired. Transfer of the data and location information is initiated by the mobile device for storage and analysis external to the mobile device.

Description

METHOD AND APPARATUS OF COLLECTING DATA FOR AGRICULTURAL ANALYSIS

BACKGROUND

Wireless (e.g., cellular) service providers and device manufacturers are continually challenged to deliver value and convenience to consumers by, for example, providing compelling network services, applications, and content, as well as user-friendly devices. Important differentiators in this industry are application and network services. In particular, these services can include agricultural service applications. Technology can be used to improve farming practices in agriculture using mobile devices.

SOME EXAMPLE EMBODIMENTS

According to one embodiment, a method comprises collecting data about an agricultural product using a mobile device; acquiring location information corresponding to the agricultural product; and initiating transfer of the data and the location information by the mobile device for storage and analysis external to the mobile device.

According to another embodiment, a computer-readable medium carries one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to perform at least the following: collecting data about an agricultural product using a mobile device; acquiring location information corresponding to the agricultural product; and initiating transfer of the data and the location information by the mobile device for storage and analysis external to the mobile device.

According to another embodiment, an apparatus comprises at least one processor, and at least one memory including computer program code. The at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following: collect data about an agricultural product using a mobile device, acquire location information corresponding to the agricultural product, and initiate transfer of the data and the location information by the mobile device for storage and analysis external to the mobile device.

According to another embodiment, an apparatus comprises means for collecting data about an agricultural product using a mobile device; means for acquiring location information corresponding to the agricultural product; and means for initiating transfer of the data and the location information by the mobile device for storage and analysis external to the mobile device.

According to another embodiment, a method comprising receiving data about an agricultural product and location information corresponding to the agricultural product from a mobile device, wherein the data specifies information about either environment, terrain, pH level, mineral level, or a combination thereof about the location information; initiating storage of the data and location information within a database; analyzing the received data using an expert system; and generating a message about the analyzed data for transmission to the mobile device.

According to another embodiment, a computer-readable medium carries one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to perform at least the following: receiving data about an agricultural product and location information corresponding to the agricultural product from a mobile device, wherein the data specifies information about either environment, terrain, pH level, mineral level, or a combination thereof about the location information; initiating storage of the data and location information within a database; analyzing the received data using an expert system; and generating a message about the analyzed data for transmission to the mobile device.

According to another embodiment, an apparatus comprises at least one processor, and at least one memory including computer program code. The at least one memory and the computer program code is configured to, with the at least one processor, cause the apparatus to perform at least the following: receive data about an agricultural product and location information corresponding to the agricultural product from a mobile device, wherein the data specifies information about either environment, terrain, pH level, mineral level, or a combination thereof about the location information, initiate storage of the data and location information within a database, analyze the received data using an expert system, and generate a message about the analyzed data for transmission to the mobile device.

According to yet another embodiment, an apparatus comprises means for receiving data about an agricultural product and location information corresponding to the agricultural product from a mobile device, wherein the data specifies information about either environment, terrain, pH level, mineral level, or a combination thereof about the location information; means for initiating storage of the data and location information within a database; means for analyzing the received data using an expert system; and means for generating a message about the analyzed data for transmission to the mobile device.

Still other aspects, features, and advantages of the invention are readily apparent from the following detailed description, simply by illustrating a number of particular embodiments and implementations, including the best mode contemplated for carrying out the invention. The invention is also capable of other and different embodiments, and its several details can be modified in various obvious respects, all without departing from the spirit and scope of the invention. Accordingly, the drawings and description are to be regarded as illustrative in nature, and not as restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments of the invention are illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings:

FIG. 1 is a diagram of a system capable of providing agricultural analysis to a user, according to one embodiment;

FIG. 2 is a flowchart of a process for analyzing agricultural information using a mobile device, according to one embodiment; FIG. 3 is a diagram of an agricultural analysis platform, according to one embodiment;

FIG. 4 is a diagram of a data capture module, according to one embodiment;

FIG. 5 is a flowchart of a process for informing a user of a agricultural analysis, according to one embodiment;

FIGs. 6A and 6B are diagrams of interfaces for receiving analysis information, according to various embodiments;

FIG. 7 is a flowchart of a process for determining multi-crop sowing advice, according to one embodiment;

FIG. 8 is a flowchart of a process for determining an estimated time of harvest of an agricultural product, according to one embodiment; FIG. 9 is a diagram of hardware that can be used to implement an embodiment of the invention;

FIG. 10 is a diagram of a chip set that can be used to implement an embodiment of the invention; and

FIG. 11 is a diagram of a mobile station (e.g., handset) that can be used to implement an embodiment of the invention.

DESCRIPTION OF PREFERRED EMBODIMENTS

A method and apparatus for improving precision farming using a mobile device. In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the invention. It is apparent, however, to one skilled in the art that the embodiments of the invention may be practiced without these specific details or with an equivalent arrangement. In other instances, well-known structures and devices are shown in block diagram form in order to avoid unnecessarily obscuring the embodiments of the invention.

Although various embodiments are described with respect to mobile devices and sensing of agricultural products, it is contemplated that the approach described herein may be used with other devices and applications.

FIG. 1 is a diagram of a system capable of providing agricultural analysis to a user, according to one embodiment. For the purposes of illustration, system 100 provides for the management of agricultural services on a user equipment. As shown in FIG. 1, system 100 comprises one or more user equipment (UEs), e.g., UEs 10Ia-IOIn, having connectivity to an agricultural analysis platform 111 via a communication network 105. The UEs 101 a- 10 In are any type of mobile terminal, fixed terminal, or portable terminal including mobile handsets, mobile phones, mobile communication devices, stations, units, devices, multimedia tablets, digital book readers, game devices, audio/video players, digital cameras/camcorders, positioning device, televisions, radio broadcasting receivers, Internet nodes, communicators, desktop computers, laptop computers, Personal Digital Assistants (PDAs), or any combination thereof. Under this scenario, the UE 101a employs a radio link to access network 105, while connectivity of UE lOln to the network 105 can be provided over a wired link. It is also contemplated that the UEs 10Ia-IOIn can support any type of interface to the user (such as "wearable" circuitry, etc.).

In one embodiment, the UE 101 can have a data capture module 103. A data capture module 103 can have sensors 113 or inputs to sensor information. For example, the data capture module 103 can include a camera, sound/ultrasound imaging, or temperature sensor. A data capture module 103 can also have a FM receiver, Bluetooth receiver, or other communications systems to receive input from one or more sensors.

By way of example, the communication network 105 of system 100 includes one or more networks such as a data network (not shown), a wireless network (not shown), a telephony network (not shown), or any combination thereof. It is contemplated that the data network may be any local area network (LAN), metropolitan area network (MAN), wide area network (WAN), the Internet, or any other suitable packet-switched network, such as a commercially owned, proprietary packet-switched network, e.g., a proprietary cable or fiber-optic network. In addition, the wireless network may be, for example, a cellular network and may employ various technologies including enhanced data rates for global evolution (EDGE), general packet radio service (GPRS), global system for mobile communications (GSM), Internet protocol multimedia subsystem (IMS), universal mobile telecommunications system (UMTS), etc., as well as any other suitable wireless medium, e.g., microwave access (WiMAX), Long Term Evolution (LTE) networks, code division multiple access (CDMA), wireless fidelity (WiFi), satellite, mobile ad-hoc network (MANET), and the like. In addition, the wireless network may be, for example, a short range network, such a Bluetooth® network, ultra wide band (UWB) network, radio frequency identification (RFID) network or infrared network (IrDA). Additionally, the communication network 105 could, in one embodiment, include a peer-to-peer distributed system that is locally organized by user (e.g., the farmers) over mobile devices 101.

By way of example, the UEs 10Ia-IOIn can communicate with the agricultural analysis platform 111 over the communication network 105 using standard protocols. The UEs 10Ia-IOIn and the platform 111 are network nodes with respect to the communication network 105. In this context, a protocol includes a set of rules defining how the network nodes within the communication network 105 interact with each other based on information sent over the communication links. The protocols are effective at different layers of operation within each node, from generating and receiving physical signals of various types, to selecting a link for transferring those signals, to the format of information indicated by those signals, to identifying which software application executing on a computer system sends or receives the information. The conceptually different layers of protocols for exchanging information over a network are described in the Open Systems Interconnection (OSI) Reference Model.

Communications between the network nodes are effected, for example, by exchanging discrete packets of data. Each packet comprises, for example, (1) header information associated with a particular protocol, and (2) payload information that follows the header information and contains information that may be processed independently of that particular protocol. In some protocols, the packet includes (3) trailer information following the payload and indicating the end of the payload information. The header includes information such as the source of the packet, its destination, the length of the payload, and other properties used by the protocol. Often, the data in the payload for the particular protocol includes a header and payload for a different protocol associated with a different, higher layer of the OSI Reference Model. The header for a particular protocol indicates, for example, a type for the next protocol contained in its payload. The higher layer protocol is said to be encapsulated in the lower layer protocol. The headers included in a packet traversing multiple heterogeneous networks, such as the Internet, include, for example, a physical (layer 1) header, a data-link (layer 2) header, an internetwork (layer 3) header and a transport (layer 4) header, and various application headers (layer 5, layer 6 and layer 7) as defined by the OSI Reference Model.

The agricultural analysis platform 111 can be used by a UE 101a application 109a to service a user's agricultural needs. In one embodiment, the agricultural analysis platform 111 can store information within an application storage module 121 for applications 109a-109n resident on the UEs 101 a- 101 n. In another embodiment, such information can be location and environmental information of a farm associated to the user. By way of example, location information includes global positioning systems (GPS), assisted global positioning systems (A- GPS), Cell of Origin, triangulation systems, and other locator systems. Environmental information can include parameters specifying temperature, wind, ultraviolet light (UV) level, humidity level, soil condition, etc.

In one embodiment, the agricultural analysis platform 111 can access remote sensing data from a remote sensing data module 115. The remote sensing data module 115 can access environmental data collected by external services such as National Aeronautics and Space Administration (NASA) and Indian Space Research Organisation (ISRO). Weather pattern shifts and forecasts can be used as an input to help determine the planting, watering, and harvesting plans of a farmer.

In another embodiment, the agricultural analysis platform 111 can access a temporal data module 117. The temporal data module 117 can store sensor data collected over time from terrestrial sensor farms 119. The sensors from the sensor farms 119 can be used to communicate directly to a UE 101 or through other means for its data to be collected by the temporal data module 117. Sensors used by the sensor farms 119 can be used to monitor environmental conditions that affect crops. For example, temperature, humidity, wind, ultraviolet light, soil humidity, soil pH, and soil mineral level sensors can be used. Sensors for conditions that have a minimal change in value over distances can be shared by a community. Sensors that have values that change more than nominally over a distance can be owned by an individual or embedded on a mobile device. Additionally, the frequency of data collection necessary will change depending on the type of sensor. For example, temperature could be collected every hour, while a pH value could be collected every day. The temporal data can be accessed using location and time coordinates.

In another embodiment, the agricultural analysis platform 111 can access an expert advice module 107. The expert advice module 107 can contain information collected by experienced farmers and scientists about agricultural success (e.g., expert system). Agricultural experts, farmers, and institutions can collate their collective knowledge over time in the database. The expert advice module 107 can also contain information about what crops have been successful in that region in the past. A farmer can additionally choose which expert to use as an option. Additionally, the advice database can give advice depending on various variables and algorithms. For example, the expert advice module 107 can recommend planting a combination of Crops X and Y for monsoon season and planting Crops X and Z during a summer season. Such information can be used decide which crops to sow, when to water, and the like. FIG. 2 is a flowchart of a process for analyzing agricultural information using a UE 101 like a mobile device, according to one embodiment. In step 201, a mobile device collects data about an agricultural product. The data collected can specify information about the environment, temperature, terrain, pH level in the soil, mineral levels in the soil, or a combination of thereof. In step 203, the mobile device acquires location information corresponding to the agricultural product. The location information can be discerned from triangulation technologies used in a position capture module 401. In step 205, the mobile device initiates transfer or transmission of agricultural product data and location information over a communications network 105 like a radio network for storage and analysis external to the mobile device. Alternatively, the data and location information can be transferred using a removable memory, e.g., memory card.

In step 207 an agricultural analysis platform 111 can receive the agricultural product data and location information sent by a mobile device. In step 209 the agricultural analysis platform 111 can initiate storage of the data and location information within an application storage module 121 or database. In step 211, the agricultural analysis platform 111 can analyze the received data using an expert system. The expert system can include an expert advice module 107. In step 213, the agricultural analysis platform 111 can generate a message about the analyzed data for transmission to a mobile device.

Under the above approach, a user (e.g., farmer) can leverage technology without significant infrastructure investment, as mobile devices used in the course of daily life can now be deployed for commercial gain, for example.

FIG. 3 is a diagram of an agricultural analysis platform 111, according to one embodiment. The agricultural analysis platform 111 can have a data collection module 301 to collect data from a UE 10Ia-IOIn, an expert advice module 107, temporal data module 117, remote sensing data module 115, or other databases with relevant agricultural information. The agricultural analysis platform 111 can access various databases through the communication network, including databases on the internet. The agricultural analysis platform 111 can include an analysis module 303 that can be used for agriculture management, multi-crop management, imaging, and estimating time of harvest. Additionally, the agriculture analysis platform 111 can have a communications module 305 to send the UE 101 audio, icon, text, and other data to be communicated to a user.

In one embodiment, the analysis module 303 can run a multi-crop management service. The service can interface with a multi-crop management application 109a residing on a UE 101a through a communication network 105. The multi-crop management application 109a can analyze data collected from a UE 101a with combined data from a temporal data module 117, a remote sensing data module 115, and an expert advice module 107. The application logic processes the data and matches a set of crops that are suited for cultivation on the farm land during requested time periods. The multi-crop management application 109a on the analysis module 303 can have a table containing minimal conditions to farm certain crops. For example, in the table below, Crop3 cannot grow if the temperature falls below 16 degrees Celsius for over two hours.

Table 1 :

Aggregated sensor data for a GPS location that the farmer is interested can be exemplified by the following table.

Table 2:

Based on data from the location, the application can deduce that Crop2 and Crop3 are suitable for cultivation on that piece of land. Cropl is not suitable for the particular piece of land because it needs a greater minimum temperature than found in the region. Additionally, a farmer can request an analysis on what conditions are necessary to grow a particular type of crop the farmer wishes to grow.

FIG. 4 is a diagram of a data capture module 103, according to one embodiment. The data capture module 103 can have sensors, a position capture module 401, an image capture module 403, and a sensor module 405. In one embodiment, the UE 101 can have a position capture module 401. A position capture module 401 can include a standard global positioning system (GPS), an assisted global positioning system (A-GPS), a Cell of Origin and/or other location extrapolation technologies, such as wireless local area network positioning systems. Standard GPS and A-GPS systems can use satellites to pinpoint the location of a UE 101. A Cell of Origin system can be used to determine the cellular tower that a cellular UE 101 is synchronized with. This information gives a coarse location of the UE 101 because the cellular tower can have a unique cellular identifier (cell-ID) that can be geographically mapped.

In another embodiment, the UE 101 can have an image capture module 403. The image capture module 403 can have a camera to capture an image. The image capture module 403 can also have a distance capture sensor, such as an infrared sensor, to capture the distance an object is from the camera when an image is captured. The image capture module 403 can also interact with the position capture module 401 to synchronize the location of an image with the image and distance data capture. A single or multiple files can be created to include the synchronized images. Images can be taken in various formats, including, but not limited to, bitmap (BMP), Joint Photographies Experts Group (JPEG), tagged image file format (TIFF), Graphics Interchange Format (GIF), and other image formats. The images of the agricultural product can be based on color, shape, etc. to determine quality of the agricultural product. Additionally, the analysis can utilize other sensed data, such as sound/ultrasound sensor systems to gather data about the product.

In another embodiment, the UE 101 can have a sensor module 405. The sensor module 405 can include sensors to measure various parameters, such as temperature, wind, ultraviolet light (UV), humidity, soil humidity, soil pH, and soil mineral level sensors or soil nutrient level sensors as well as external sensor input logic and tuning logic. External sensor input logic can include various types of inputs, both wired and wireless, to communicate with sensors and input data can be processed or unprocessed.

In one embodiment, tuning logic can include a frequency modulation (FM) transceiver to send and receive information to another FM device, such as sensors 407a-407n. It is contemplated that other modulation schemes and/or radio technologies can be utilized. Such an FM device can be a sensor stick 407n. A sensor apparatus (e.g., stick) 407n can be inserted in the soil of a plot of farm land. The sensor stick 407n can have a transceiver 409 to send and receive data to a UE 101, above-ground 411 and below-ground 413 sensors, and a processing module 415 to process sensor information before sending information to a UE 101. The sensor stick 407n can be placed at a depth where sensors on the lower end of the stick can be underground. The sensor stick 407n can also be placed so that sensors can be above-ground. A farmer can use single or multiple sensor sticks 407n on a farm. Each sensor stick 407n can have a unique color or frequency on which it can transmit its values of parameters. After placing the stick, a farmer can use a tuning application to match respective colors and names to sensor sticks 407n. Naming a sensor stick 407n can be voice-based or text-based. The sensor stick 407n can be paired to a UE 101 to simplify use for a user. Additionally, a geographic map of the area in which sensor sticks 407n are placed can be shown to a user indicating the placement of the sensor sticks 407n. A sensor stick 407n does not have to be in the form of a stick, but can also include a device, such as a sensor cluster having a sensor, a means to process sensor information, and a transmitter to transmit the collected information.

FIG. 5 is a flowchart of a process for informing a user of an agricultural analysis, according to one embodiment. At step 501, a UE 101 can be paired to one or more installed sensor sticks to simplify the interface for future transactions. Pairing can be a link or a bond between the UE 101 and the sensor stick 407n. Pairing can include an application on the UE 101 creating a unique identifier of the sensor stick 407n to track and store data regarding the sensor stick 407n. This can be later used to remember the position, data obtained from the sensor stick 407n, and user preferences. During the pairing process, the user can determine if user preferences, such as whether the user wants a voice, icon, or text-based interface. The user can also choose to color code sensor sticks 407n so that other workers can easily follow sensor stick 407n advice. The sensor stick 407n can gather environmental and terrestrial data about agricultural products. The sensor stick 407n can then process the data from the sensors to determine what conditions affect the agricultural products. Exemplary conditions include the soil being dry and humidity levels dropping. In one embodiment, the sensor sticks 407n can have a storage memory to keep sensor readings to determine patterns such as humidity levels dropping. The sensor stick 407n can also process sensor data and crop information to determine farming instructions and priorities such as watering and fertilizing. At step 503, the sensor stick 407n relays its processed information, sensor data, and/or recommendations to the UE 101. At step 505, the UE 101 formats the recommendation based on user preferences. At step 507, the UE 101 can inform the user of environmental and terrestrial conditions and any processed recommendations based on the user's preferences.

Under the above approach, a user (e.g., farmer) can leverage technology without substantial infrastructure investment. A farmer can use his regular mobile device to obtain sensor data while passing through his farm. Additionally, the farmer may not have to stop to obtain relevant data. Additionally, the farmer can select an icon-based or audible interface if the farmer or a farmer's employee is not literate.

FIGs. 6A and 6B are diagrams of interfaces for receiving analysis information, according to various embodiments. FIG. 6A shows a UE 101 outputting data through audio communication. Output data can be received by a user, such as a farmer, in the farmer's native language 601, which can be selected by the farmer. A sensor stick 407n can convert sensor values of parameters into voice prompts using a text to speech engine and transmit the voice prompts over FM radio. A farmer who is tuned into that frequency can listen to the sensor stick 407n (i.e. "soil is dry," "air humidity is going down" etc.). In FIG. 6A, the farmer is tuned into a frequency that Bhura is transmitting on. The sensor stick 407n can identify itself with a name before relaying sensor data (i.e. "I am Bhura"). The farmer can then take action based on the reported conditions. This approach provides ease of use, and thus, no specialized skills are required. For example, because the system is audible, illiteracy is not an issue.

FIG. 6B shows text-based 621 and icon-based 623 interfaces to communicate the same information. For instance "Soil is very dry" and "Soil nutrients low" can be communicated via text 621 or icons 623. A sensor stick's processing module 415 and transmitter 409 can encode sensor values of parameters and transmit the values over FM radio. The values can be decoded and converted into respective icons, visual grammar, or text that can be understood by the farmer. The farmer can look at the user interface where all sensor stick 407n values are visualized. The list of sensor stick 407n parameters can be browsed, like the contacts or messaging applications on a cell phone that a farmer may be familiar with. In this mode, a farmer can quickly browse through values of the parameters and be attentive to required areas of the farm.

FIG. 7 is a flowchart of a process for determining multi-crop sowing advice, according to one embodiment. The process begins with a user, such as a farmer requesting an agricultural analysis platform 111 to perform an analysis of a geographic location to determine which crops to plant on the farmer's land. At step 701, communication is established with the agriculture analysis platform 111. At step 703, the platform receives the geographic location of the UE 101. The user can be standing at the location and have a position capture module 401 determine coordinates compatible with the platform's services. This location data can then be sent to the platform. At step 705, the platform requests and receives temporal, environmental and terrestrial sensor data for the UE's 101 geographic location from a temporal data module 117. This data can come from farms in the area registered with the service or from the farmer's farm. At step 707, the platform requests and receives remote sensing data for the UE's 101 geographic location from one or more remote sensing data modules 115. Remote sensing data can come from third parties, such as organizations like NASA and ISRO. At step 709, the platform analyzes the received data using an expert advice module 107. Advice can be given as to the crops that will grow on the land, the best crops that can grow on the land, and which crops can grow in harmony on a single plot of land. At step 711, the platform outputs the suggested multi-crop advice to the UE 101. The UE 101 can then communicate the advice to the user.

With the above approach, a user (e.g., farmer), for instance, can leverage technology to maximize use of the user's property. Moreover, a farmer can advantageously grow multiple crops on a piece of land during a single or multiple seasons. A farmer can now use technology to obtain farming knowledge from across the world while standing in his farmland.

In one embodiment, a farmer can use a UE 101 with a built-in precision farming imaging client to estimate the proper time to harvest his agricultural products. The farmer can register his UE 101 with a service to upload his user-specific data to be analyzed. The name and phone number of the farmer could be entered by the farmer to the service provider, who could create a unique Farmer ID for that particular individual.

An estimated time of harvest application on the UE 101 can use an image capture module 403 and a position capture module 401 in conjunction to estimate a proper time of harvest. A camera can take the image of a fruit (e.g., apples, grapes, plumbs, etc.), vegetable (e.g., tomatoes, carrots, etc.), or other green stock such astimber. The image capture module 403 can also capture the distance of the green stock from the camera lens using an infrared sensor or other distance capture device when an image is taken. Additionally, the position capture module 401 can capture the location of the UE 101 when the image is taken. The application can coordinate the image, distance, and location capture features of a UE 101. The UE 101 can send the collected data to an agricultural analysis platform 111 by multimedia messaging service (MMS), general packet radio service (GPRS), or other means via the communication network 105 to analyze estimated time of harvest.

The data collection module 301 on the agricultural analysis platform 111 can receive data collected by a UE 101. An estimated time of harvest application on the analysis module 303 can analyze the received data. A geographic information system (GIS) can be used to map the position of the UE 101 and its corresponding image. GIS technology could be implemented to load a UE 101 with geographic information about the farming areas of individual farmers located at a given region. The map can be separated into plots of land. A farmer's plots can be identified using unique Farming land IDs for the farmer. Additionally, other identifiers can be used to identify plots of neighboring farmers. The plots can be associated with their respective geo-coordinates. A plot can be labeled with dimensions and size that can be determined by the application or input by the farmer. The plot can be updated with information on estimated time of harvest based on the requests by the farmer.

The estimated time of harvest application can also use an imaging schemes application to do additional analysis on the image. The imaging schemes application can extrapolate the size of the green stock image using common imaging schemes with the image and distance data as inputs. This can determine the size and diameter for the green stock. Additionally, imaging schemes can be used to extrapolate the color of the green stock. This information can be combined in an image recognition algorithm to determine the type of green stock. Alternatively, these steps can be performed on the UE 101. The farmer can have the option to confirm the results. The color and size of the green stock can be analyzed to determine ripeness and readiness for harvest.

In one embodiment, the estimated time of harvest can be determined by the diameter of the green stock. An expert advice module 107 can maintain a database of estimated time of harvest information for a variety of different green stock objects. The database could contain average values for various relevant parameters for a given region. For instance, in South-India the diameter of a mature, harvestable grape could be 12mm, and the red green blue (RGB) code for a ripe grape could be 205, 205, 0. The estimated time of harvest application can also use time of planting, weather conditions, and previous requests as input in determining the estimated time of harvest for a plot of land.

Once a farmer requests an estimated time of harvest, the UE 101 can show a geographical map to the farmer containing estimated time of harvest data. Below is an exemplary table showing possible estimated time of harvest (ETH) data received by a farmer on his UE 101.

Table 3:

In the above table, the request ID field represents a farmer's request for an estimated time of harvest. The Farming land ID field is the identification of the plot the farmer was standing at when the farmer requested the estimated time of harvest. The Farmer ID field is a unique identifier to the farmer making the estimated time of harvest request. Crop field is the type of green stock that is captured by the image during an estimated time of harvest request. ETH field represents the estimated time of harvest for the request. Volume field represents the estimated mass of the green stock once harvested. Once this data is collected, it can be used to broker the sale of green stock before it is harvested.

The application can serve as an intermediary between farmers that want to sell a green stock product and buyers who wish to purchase the green stock product. The brokerage system can offer a reliable anticipatory brokerage of green stock. A marketplace service can be interface with the estimated time of harvest application to facilitate conducting commerce relating to the green stock. The green stock image and estimated time of harvest can be transmitted to such a marketplace service where sellers and buyers can negotiate commerce relating to an agricultural product, like green stock.

FIG. 8 is a flowchart of a process running on an agricultural analysis platform 111 for determining an estimated time of harvest of an agricultural product, according to one embodiment. A user, such as a farmer, can begin the process by going to a plot of land, initializing the ETH application on the farmer's UE 101 , and using the image capture feature of the ETH application to take an image of a green stock. The image capture feature of the ETH application can capture the image, the distance to the green stock, and the geographic location of the UE 101. The image capture data can be sent to an agricultural analysis platform 111. The agricultural analysis platform 111 can receive the image 801, the distance data 803, and the geographic location data 805 from the UE 101. This ETH data can be stored in an application storage database for future use. Additionally, data can be collected from the application storage database for use in estimating the time of harvest. At step 807, the agricultural analysis platform 111 can then recognize the size, color, and/or type of the green stock using known imaging techniques. The farmer can also input the type of green stock manually.

At step 809, the size, color, time of planting, and other relevant attributes of the green stock can be used to determine the ETH of the green stock. For instance, a plot of land at a location may have a current ETH using data collected over time; this ETH data can be used in conjunction with the new data collected to update the ETH for the location. The agricultural analysis platform 111 can also format the ETH data into convenient maps with requested ETH data available at various point of the map.

With the described process, a user (e.g., farmer) can effectively employ technology to maximize profits and optimize utilization of farming land. Because the farmer can quickly determine the ETH of a plot of land, the fanner can begin planning future use of the land before the harvest. Additionally, the farmer can use the marketplace service to sell his agricultural product at a later date from his farm plot.

Additionally, an application could be used to determine the quality of a harvest. If the green stock is deemed to be unhealthy, the application can determine if additional fertilizer or watering is needed. This information could also be used in the marketplace service for the benefit of buyers.

The processes described herein for providing agricultural analysis services for these applications may be implemented via software, hardware, e.g., general processor, Digital Signal Processing (DSP) chip, an Application Specific Integrated Circuit (ASIC), Field Programmable Gate Arrays (FPGAs), etc., firmware or a combination thereof. Such exemplary hardware for performing the described functions is detailed below.

FIG. 9 illustrates a computer system 900 upon which an embodiment of the invention may be implemented. Computer system 900 is programmed to provide applications, e.g. multi-crop as described herein and includes a communication mechanism such as a bus 910 for passing information between other internal and external components of the computer system 900. Information (also called data) is represented as a physical expression of a measurable phenomenon, for example electric voltages, but including, in other embodiments, such phenomena as magnetic, electromagnetic, pressure, chemical, biological, molecular, atomic, subatomic and quantum interactions. For example, north and south magnetic fields, or a zero and non-zero electric voltage, represent two states (0, 1) of a binary digit (bit). Other phenomena can represent digits of a higher base. A superposition of multiple simultaneous quantum states before measurement represents a quantum bit (qubit). A sequence of one or more digits constitutes digital data that is used to represent a number or code for a character. In some embodiments, information called analog data is represented by a near continuum of measurable values within a particular range.

A bus 910 includes one or more parallel conductors of information so that information is transferred quickly among devices coupled to the bus 910. One or more processors 902 for processing information are coupled with the bus 910.

A processor 902 performs a set of operations on information related to agricultural analysis. The set of operations include bringing information in from the bus 910 and placing information on the bus 910. The set of operations also include, for example, comparing two or more units of information, shifting positions of units of information, and combining two or more units of information, such as by addition or multiplication or logical operations like OR, exclusive OR (XOR), and AND. Each operation of the set of operations that can be performed by the processor is represented to the processor by information called instructions, such as an operation code of one or more digits. A sequence of operations to be executed by the processor 902, such as a sequence of operation codes, constitute processor instructions, also called computer system instructions or, simply, computer instructions. Processors may be implemented as mechanical, electrical, magnetic, optical, chemical or quantum components, among others, alone or in combination.

Computer system 900 also includes a memory 904 coupled to bus 910. The memory 904, such as a random access memory (RAM) or other dynamic storage device, stores information including processor instructions for analyzing agricultural information. Dynamic memory allows information stored therein to be changed by the computer system 900. RAM allows a unit of information stored at a location called a memory address to be stored and retrieved independently of information at neighboring addresses. The memory 904 is also used by the processor 902 to store temporary values during execution of processor instructions. The computer system 900 also includes a read only memory (ROM) 906 or other static storage device coupled to the bus 910 for storing static information, including instructions, that is not changed by the computer system 900. Some memory is composed of volatile storage that loses the information stored thereon when power is lost. Also coupled to bus 910 is a non- volatile (persistent) storage device 908, such as a magnetic disk, optical disk or flash card, for storing information, including instructions, that persists even when the computer system 900 is turned off or otherwise loses power.

Information, including instructions for analyzing agricultural products, is provided to the bus 910 for use by the processor from an external input device 912, such as a keyboard containing alphanumeric keys operated by a human user, or a sensor. A sensor detects conditions in its vicinity and transforms those detections into physical expression compatible with the measurable phenomenon used to represent information in computer system 900. Other external devices coupled to bus 910, used primarily for interacting with humans, include a display device 914, such as a cathode ray tube (CRT) or a liquid crystal display (LCD), or plasma screen or printer for presenting text or images, and a pointing device 916, such as a mouse or a trackball or cursor direction keys, or motion sensor, for controlling a position of a small cursor image presented on the display 914 and issuing commands associated with graphical elements presented on the display 914. In some embodiments, for example, in embodiments in which the computer system 900 performs all functions automatically without human input, one or more of external input device 912, display device 914 and pointing device 916 is omitted. In the illustrated embodiment, special purpose hardware, such as an application specific integrated circuit (ASIC) 920, is coupled to bus 910. The special purpose hardware is configured to perform operations not performed by processor 902 quickly enough for special purposes. Examples of application specific ICs include graphics accelerator cards for generating images for display 914, cryptographic boards for encrypting and decrypting messages sent over a network, speech recognition, and interfaces to special external devices, such as robotic arms and medical scanning equipment that repeatedly perform some complex sequence of operations that are more efficiently implemented in hardware.

Computer system 900 also includes one or more instances of a communications interface 970 coupled to bus 910. Communication interface 970 provides a one-way or two-way communication coupling to a variety of external devices that operate with their own processors, such as printers, scanners and external disks. In general the coupling is with a network link 978 that is connected to a local network 980 to which a variety of external devices with their own processors are connected. For example, communication interface 970 may be a parallel port or a serial port or a universal serial bus (USB) port on a personal computer. In some embodiments, communications interface 970 is an integrated services digital network (ISDN) card or a digital subscriber line (DSL) card or a telephone modem that provides an information communication connection to a corresponding type of telephone line. In some embodiments, a communication interface 970 is a cable modem that converts signals on bus 910 into signals for a communication connection over a coaxial cable or into optical signals for a communication connection over a fiber optic cable. As another example, communications interface 970 may be a local area network (LAN) card to provide a data communication connection to a compatible LAN, such as Ethernet. Wireless links may also be implemented. For wireless links, the communications interface 970 sends or receives or both sends and receives electrical, acoustic or electromagnetic signals, including infrared and optical signals, that carry information streams, such as digital data. For example, in wireless handheld devices, such as mobile telephones like cell phones, the communications interface 970 includes a radio band electromagnetic transmitter and receiver called a radio transceiver. In certain embodiments, the communications interface 970 enables connection to the communication network 105 for analyzing agricultural product information.

The term computer-readable medium is used herein to refer to any medium that participates in providing information to processor 902, including instructions for execution. Such a medium may take many forms, including, but not limited to, non-volatile media, volatile media and transmission media. Non-volatile media include, for example, optical or magnetic disks, such as storage device 908. Volatile media include, for example, dynamic memory 904. Transmission media include, for example, coaxial cables, copper wire, fiber optic cables, and carrier waves that travel through space without wires or cables, such as acoustic waves and electromagnetic waves, including radio, optical and infrared waves. Signals include man-made transient variations in amplitude, frequency, phase, polarization or other physical properties transmitted through the transmission media. Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, CDRW, DVD, any other optical medium, punch cards, paper tape, optical mark sheets, any other physical medium with patterns of holes or other optically recognizable indicia, a RAM, a PROM, an EPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wave, or any other medium from which a computer can read.

FIG. 10 illustrates a chip set 1000 upon which an embodiment of the invention may be implemented. Chip set 1000 is programmed to process agricultural information associate as described herein and includes, for instance, the processor and memory components described with respect to FIG. 10 incorporated in one or more physical packages. By way of example, a physical package includes an arrangement of one or more materials, components, and/or wires on a structural assembly (e.g., a baseboard) to provide one or more characteristics such as physical strength, conservation of size, and/or limitation of electrical interaction.

In one embodiment, the chip set 1000 includes a communication mechanism such as a bus 1001 for passing information among the components of the chip set 1000. A processor 1003 has connectivity to the bus 1001 to execute instructions and process information stored in, for example, a memory 1005. The processor 1003 may include one or more processing cores with each core configured to perform independently. A multi-core processor enables multiprocessing within a single physical package. Examples of a multi-core processor include two, four, eight, or greater numbers of processing cores. Alternatively or in addition, the processor 1003 may include one or more microprocessors configured in tandem via the bus 1001 to enable independent execution of instructions, pipelining, and multithreading. The processor 1003 may also be accompanied with one or more specialized components to perform certain processing functions and tasks such as one or more digital signal processors (DSP) 1007, or one or more application-specific integrated circuits (ASIC) 1009. A DSP 1007 typically is configured to process real-world signals (e.g., sound) in real time independently of the processor 1003. Similarly, an ASIC 1009 can be configured to performed specialized functions not easily performed by a general purposed processor. Other specialized components to aid in performing the inventive functions described herein include one or more field programmable gate arrays (FPGA) (not shown), one or more controllers (not shown), or one or more other special-purpose computer chips.

The processor 1003 and accompanying components have connectivity to the memory 1005 via the bus 1001. The memory 1005 includes both dynamic memory (e.g., RAM, magnetic disk, writable optical disk, etc.) and static memory (e.g., ROM, CD-ROM, etc.) for storing executable instructions that when executed perform the inventive steps described herein to provide analysis of agricultural products. The memory 1005 also stores the data associated with or generated by the execution of the inventive steps.

FIG. 11 is a diagram of exemplary components of a mobile station (e.g., handset) capable of operating in the system of FIG. 1, according to one embodiment. Generally, a radio receiver is often defined in terms of front-end and back-end characteristics. The front-end of the receiver encompasses all of the Radio Frequency (RF) circuitry whereas the back-end encompasses all of the base-band processing circuitry. Pertinent internal components of the telephone include a Main Control Unit (MCU) 1103, a Digital Signal Processor (DSP) 1105, and a receiver/transmitter unit including a microphone gain control unit and a speaker gain control unit. A main display unit 1107 provides a display to the user in support of various applications and mobile station functions, such as multi-crop. An audio function circuitry 1109 includes a microphone 1111 and microphone amplifier that amplifies the speech signal output from the microphone 1111. The amplified speech signal output from the microphone 1111 is fed to a coder/decoder (CODEC) 1113.

A radio section 1115 amplifies power and converts frequency in order to communicate with a base station, which is included in a mobile communication system, via antenna 1117. The power amplifier (PA) 1119 and the transmitter/modulation circuitry are operationally responsive to the MCU 1103, with an output from the PA 1119 coupled to the duplexer 1121 or circulator or antenna switch, as known in the art. The PA 1119 also couples to a battery interface and power control unit 1120.

In use, a user of mobile station 1101 speaks into the microphone 1111 and his or her voice along with any detected background noise is converted into an analog voltage. The analog voltage is then converted into a digital signal through the Analog to Digital Converter (ADC) 1123. The control unit 1103 routes the digital signal into the DSP 1105 for processing therein, such as speech encoding, channel encoding, encrypting, and interleaving. In one embodiment, the processed voice signals are encoded, by units not separately shown, using a cellular transmission protocol such as global evolution (EDGE), general packet radio service (GPRS), global system for mobile communications (GSM), Internet protocol multimedia subsystem (IMS), universal mobile telecommunications system (UMTS), etc., as well as any other suitable wireless medium, e.g., microwave access (WiMAX), Long Term Evolution (LTE) networks, code division multiple access (CDMA), wireless fidelity (WiFi), satellite, and the like.

The encoded signals are then routed to an equalizer 1125 for compensation of any frequency-dependent impairments that occur during transmission though the air such as phase and amplitude distortion. After equalizing the bit stream, the modulator 1127 combines the signal with a RF signal generated in the RF interface 1129. The modulator 1127 generates a sine wave by way of frequency or phase modulation. In order to prepare the signal for transmission, an up-converter 1131 combines the sine wave output from the modulator 1127 with another sine wave generated by a synthesizer 1133 to achieve the desired frequency of transmission. The signal is then sent through a PA 1119 to increase the signal to an appropriate power level. In practical systems, the PA 1119 acts as a variable gain amplifier whose gain is controlled by the DSP 1105 from information received from a network base station. The signal is then filtered within the duplexer 1121 and optionally sent to an antenna coupler 1135 to match impedances to provide maximum power transfer. Finally, the signal is transmitted via antenna 1117 to a local base station. An automatic gain control (AGC) can be supplied to control the gain of the final stages of the receiver. The signals may be forwarded from there to a remote telephone which may be another cellular telephone, other mobile phone or a land-line connected to a Public Switched Telephone Network (PSTN), or other telephony networks.

Voice signals transmitted to the mobile station 1101 are received via antenna 1117 and immediately amplified by a low noise amplifier (LNA) 1137. A down-converter 1139 lowers the carrier frequency while the demodulator 1141 strips away the RF leaving only a digital bit stream. The signal then goes through the equalizer 1125 and is processed by the DSP 1105. A Digital to Analog Converter (DAC) 1143 converts the signal and the resulting output is transmitted to the user through the speaker 1145, all under control of a Main Control Unit (MCU) 1103— which can be implemented as a Central Processing Unit (CPU) (not shown).

The MCU 1103 receives various signals including input signals from the keyboard 1147. The keyboard 1147 and/or the MCU 1103 in combination with other user input components (e.g., the microphone 1111) comprise a user interface circuitry for managing user input. The MCU 1103 runs a user interface software to facilitate user control of at least some functions of the mobile station 1101 according to, for example, an multi-touch user interface. The MCU 1103 also delivers a display command and a switch command to the display 1107 and to the speech output switching controller, respectively. Further, the MCU 1103 exchanges information with the DSP 1105 and can access an optionally incorporated SIM card 1149 and a memory 1151. In addition, the MCU 1103 executes various control functions required of the station. The DSP 1105 may, depending upon the implementation, perform any of a variety of conventional digital processing functions on the voice signals. Additionally, DSP 1105 determines the background noise level of the local environment from the signals detected by microphone 1111 and sets the gain of microphone 1111 to a level selected to compensate for the natural tendency of the user of the mobile station 1101. The CODEC 1113 includes the ADC 1123 and DAC 1143. The memory 1151 stores various data including call incoming tone data and is capable of storing other data including music data received via, e.g., the global Internet. The software module could reside in RAM memory, flash memory, registers, or any other form of writable storage medium known in the art. The memory device 1151 may be, but not limited to, a single memory, CD, DVD, ROM, RAM, EEPROM, optical storage, or any other non-volatile storage medium capable of storing digital data.

An optionally incorporated SIM card 1149 carries, for instance, important information, such as the cellular phone number, the carrier supplying service, subscription details, and security information. The SIM card 1149 serves to identify the mobile station 1101 on a radio network. The card 1149 also contains a memory for storing a personal telephone number registry, text messages, and user specific mobile station settings.

While the invention has been described in connection with a number of embodiments and implementations, the invention is not so limited but covers various obvious modifications and equivalent arrangements, which fall within the purview of the appended claims. Although features of the invention are expressed in certain combinations among the claims, it is contemplated that these features can be arranged in any combination and order.

Claims

CLAIMS WHAT IS CLAIMED IS:

1. A method comprising: collecting data about an agricultural product using a mobile device; acquiring location information corresponding to the agricultural product; and causing at least in part processing of the data and the location information.

2. A method according to claim 1, wherein the data specifies information about environment, terrain, pH level, mineral level, or a combination thereof.

3. A method according to any of claims 1 or 2, further comprising: tuning, using a tuning application on the mobile device, to a particular frequency to receive the data from a sensor corresponding to the agricultural product.

4. A method of claim 3, further comprising: initiating pairing with a plurality of sensors including the sensor; and assigning an identifier to each of the sensors.

5. A method according to any of claims 1 to 4, wherein the collection of data includes capturing a digital image of the agricultural product, or capturing sensed data using either sound, ultrasound, or infrared.

6. A method according to any of claims 1 to 5, further comprising: causing at least in part a generating a request or a retrieving relating to estimated time of harvest of the agricultural product.

7. A method of claim 6, further comprising: causing at least in part a receiving or a processing the estimated time of harvest in response initiating transmission of or causing at least in part processing of the image and estimated time of harvest.

8. A method according to any of claims 1 to 7, wherein the collection of data is performed periodically to establish a historical record, the method further comprising: causing at least in part receiving or causing at least in part processing information on type of agricultural product to utilize for the location information based on analysis of the historical record.

9. An apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following, collect data about an agricultural product using a mobile device, acquire location information corresponding to the agricultural product, and initiate transfer of the data and the location information by the mobile device for storage and analysis external to the mobile device.

10. An apparatus according to claim 9, wherein the data specifies information about either environment, terrain, pH level, mineral level, or a combination thereof.

11. An apparatus according to any of claims 9 to 10, wherein the apparatus is further caused to: tune, using a tuning application on the mobile device, to a particular frequency to receive the data from a sensor corresponding to the agricultural product.

12. An apparatus of claim 11, wherein the apparatus is further caused to: initiate pairing with a plurality of sensors including the sensor; and assign an identifier to each of the sensors.

13. An apparatus according to any of claims 9 to 12, wherein the collection of data includes capturing a digital image of the agricultural product, or capturing sensed data using either sound, ultrasound, or infrared.

14. An apparatus according to any of claims 9 to 13, wherein the apparatus is further caused to: generate a request relating to estimated time of harvest of the agricultural product.

15. An apparatus according to claim 14, wherein the apparatus is further caused to: receive the estimated time of harvest in response to the request; and initiate transmission of the image and estimated time of harvest to a marketplace service for conducting commerce relating to the agricultural product.

16. An apparatus according to any of claims 9 to 15, wherein the collection of data is performed periodically to establish a historical record, the wherein the apparatus is further caused to: receive information on type of agricultural product to utilize for the location information based on analysis of the historical record.

17. An apparatus according to any of claims 9 to 16, wherein the mobile device is a mobile phone comprising: user interface circuitry and user interface software configured to facilitate user control of at least some functions of the mobile phone through use of a display and configured to respond to user input; and a display and display circuitry configured to display at least a portion of a user interface of the mobile phone, the display and display circuitry configured to facilitate user control of at least some functions of the mobile phone.

18. A method comprising: receiving data about an agricultural product and location information corresponding to the agricultural product from a mobile device, wherein the data specifies information about either environment, terrain, pH level, mineral level, or a combination thereof about the location information; initiating storage of the data and location information within a database; analyzing the received data using an expert system; and generating a message about the analyzed data for transmission to the mobile device.

19. A method according to claim 18, wherein the data includes a digital image of the agricultural product, the method further comprising: determining an estimated time of harvest of the agricultural product.

20. An apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following, receive data about an agricultural product and location information corresponding to the agricultural product from a mobile device, wherein the data specifies information about either environment, terrain, pH level, mineral level, or a combination thereof about the location information, initiate storage of the data and location information within a database, analyze the received data using an expert system, and generate a message about the analyzed data for transmission to the mobile device.

21. An apparatus according to claim 20, wherein the data includes a digital image of the agricultural product, the apparatus being further caused to: determine an estimated time of harvest of the agricultural product.

22. An apparatus comprising means for performing the method of any of claims 1-8 or 26.

23. An apparatus comprising means for performing the method of any of claims 18-19.

24. A computer program that when executed causes an apparatus to perform the method according to any of claims 1 to 8 or 26.

25. A computer program that when executed causes an apparatus to perform the method according to any of claims 18 to 19.

26. The method of any of claims 1-8 further comprising initiating transfer of the data and the location information by the mobile device for storage and analysis external to the mobile device.

27. A method comprising facilitating access to an interface for accessing a service, the service configured to receive data about an agricultural product and location information corresponding to the agricultural product from a mobile device, wherein the data specifies information about at least environment, terrain, pH level, mineral level, or a combination thereof about the location information; initiate storage of the data and location information within a database; analyze the received data using an expert system; and generate a message about the analyzed data for transmission to the mobile device.

28. A method according to claim 27, wherein the data includes a digital image of the agricultural product, the service further configured to: determine an estimated time of harvest of the agricultural product.