Integrated IoT (Internet of Things) system solution for smart agriculture management

• US 10,728,336 B2
• Filed: 03/07/2017
• Issued: 07/28/2020
• Est. Priority Date: 03/04/2016
• Status: Active Grant

• Current Assignee: Sabrina Akhtar
• Original Assignee: Sabrina Akhtar
• Inventors: Akhtar, Sabrina
• Primary Examiner(s): Zarroli, Michael C
• Application Number:
  US15/451,420
• Publication Number:
  US 20180262571A1
• Time in Patent Office: 1,239 Days
• CPC Class Codes: A01G 25/16 Control of watering
• CPC Class Codes: B64U 2101/00 UAVs specially adapted for particular uses or applications
• CPC Class Codes: B64U 2101/30 for imaging, photography or videography
• CPC Class Codes: B64U 2101/40 for agriculture or forestry operations
• CPC Class Codes: G05B 13/0275 using fuzzy logic only
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06Q 10/06313 Resource planning in a project environment
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: G06Q 50/02 Agriculture; Fishing; Forestry; Mining
• CPC Class Codes: G16Y 10/05 Agriculture
• CPC Class Codes: H04L 67/025 for remote control or remote monitoring of applications
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/38 for collecting sensor information
• CPC Class Codes: H04W 4/70 Services for machine-to-machine communication [M2M] or machine type communication [MTC]
• CPC Class Codes: H04W 84/18 Self-organising networks, e.g. ad-hoc networks or sensor networks
• CPC Class Codes: Y02P 30/00 Technologies relating to oil refining and petrochemical industry

Abstract

An end to end integrated technology solution available to increase overall crop yield and a communication platform to connect growers with the marketplace and an infrastructure for agriculture management, logistics, storage, distribution and delivery. Offering a global solution to this problem that provides a consolidated and integrated IoT (Internet of Things) system where data collection, monitoring, control and communication platform are managed using a single platform. An agricultural IoT monitoring device based on wireless mesh network sensing, where this device can monitor the temperature, humidity, vibration and other parameters of an agricultural cultivation base. The device is designed with a microcontroller, a sensing unit, WiFi module, LoRa communication network where it uses WiFi Mesh Network or LoRaWAN to capture real-time data for remote viewing and analyzing intelligence data for preventive actions. This single IoT system platform is providing solution for agriculture and various applications.

Claims

1. An integrated hardware and software IoT (Internet of Things) platform equipped with Artificial Intelligence where agricultural data is collected and monitored in real time remotely which provides predictive data analytics to proactively trigger preventive actions automatically:

This consolidated IoT platform provides real-time data on crop growth, soil condition, pesticide control, fertilizer selection, crop selection, crop yield, greenhouse, urban farm, garden &

lawn output such as crop climate and weather data;

this platform comprises;

A hardware portion that is called the Lifeline Unit, functions as a Field system, Monitor System, Control System and Communication System that provides a solution to collect and monitor agriculture data in real time;

the field image data is collected using a kite guidance system, infrared imaging, satellite or UAV;

Data is viewed on remote computers, laptop or handheld devices such as tablet or smartphone wherein data can be accessed both onsite or remotely;

The Field System comprises the Lifeline Unit, which is placed on the field equipped with a microcontroller board, which collects raw data from sensors that are embedded in the soil;

The platform uses embedded WiFi or LoRa (low power long range communication protocol) module on the Lifeline unit to send field data using the WiFi Mesh Network or LoRaWAN to a central hub (IoT gateway) where the data is processed for any actions based on algorithms that have been set;

The Monitor System comprises data that is sent in real time from the Lifeline Unit and it is processed at the IoT edge processing in the central hub (IoT gateway) then it is sent to a software interface for data storage and analytics namely cloud computing where data is sent in real time where users can access remotely;

The Control System comprises data analytics software that uses an artificial intelligence model for pattern recognition and alert the action module connected to the sprayer and drip irrigation system to take preventive actions such as watering when the soil is dry or engaging a kite guidance system or UAV (unmanned aerial vehicle) or infrared camera to take images of any drought condition in the field;

The Communication System comprises a communication and social media networking platform to connect growers to the market-place;

It uses Lifeline Unit with WiFi mesh network and satellite GPS where crop mapping data is collected in real time that is sent to the cloud via the internet where a social network application platform is provided for growers to connect to the market-place;

The Communication System also comprises logistics optimization for food storage, food tracking, distribution and food delivery to the marketplace;

Data is collected via Asset Tracking Sensors, which has a built-in GPS module to send signals of the said crop (food) while in transit and is displayed in real time on the communication platform;

The sensors are placed strategically on the delivery vehicles or on the cartons of the food bin;

In addition, temperature and humidity sensors are placed in the food storage facility along the food delivery route to the marketplace to minimize spoilage and track inventory in real-time via the communication system;

The integrated IoT system flow consists of;

Field System, Monitoring System, Control System and Communication System;

below is further details on each system;

Field System;

Lifeline Unit has a weather station with solar panels, the microcontroller boards are mounted onto the unit for sensor reading;

the WiFi unit is connected to the unit for mesh network, grow LED lights are also mounted with a controller;

This unit is then connected to a sensor module and the sensor module is embedded into the soil;

the field system also has drip and spray irrigation system equipped with microcontroller board for automatic water dispensing based on the soil moisture data from the Lifeline Unit;

Monitoring System;

Field data is monitored in real-time via sensors in the soil and the weather sensors that are connected to the microcontroller board, it sends raw physical data to WiFi mesh network or LoRa (long range) WAN which uses a gateway hub network to consolidate field data and send it to cloud;

It is then post processed to be viewed in a dashboard inside the software app downloaded in the smartphone;

Control System;

The control system field data and check against controlled parameters set in the data analytics in the software applications where Artificial intelligence modeling is used to mitigate preventive and predictive action;

The control valve gets triggered if the soil moisture data is below a moisture threshold set in the control parameter;

The drip system microcontroller gets activated from the threshold data;

The microcontroller then sends a signal to the controller valve and water is sprayed through the drip irrigation system on the field, similarly, aerial data collection is triggered when large swaths of land show change in field data such as moisture level, yield loss, smoke detection;

This activates the kite guidance system or drone to launch and bring back aerial footage for real-time viewing remotely;

The control system also turns on LED grow lights and fans are turned on based on the control parameters such as;

time of day and illumination data;

The system also analyzes data for any preventive maintenance needed and sends alerts to equipment management team via SMS text message;

Communication System;

The communication system is a software application interface that can be viewed on any mobile device (laptop or tablet or smartphone) with remote access capability;

Data analytics is run on this application where artificial intelligence modeling is applied on the field data to determine predictive maintenance and crop yield forecasting;

The data is displayed in charts viewed in a dashboard for key insights;

Based on the predictive data, further actions are performed automatically using application programming interface (API), for example, seeds are automatically ordered to the seed company based on predictive data;

It also connects farmers to the marketplace and other farmers in their local community to exchange seeds or share any information via instant messaging or video conferencing;

The communication system also displays logistics and real-time tracking of the inventory on route to the marketplace;

Since this Lifeline Unit is mobile, it can be installed in remote locations where it is outfitted with various types of sensors that can be integrated to collect data for various applications and usage.

2. The said IoT system in claim 1 is applicable for Geotechnical soil survey, geotechnical investigations, mineral exploration, geotechnical drilling including various soil testing to remotely provide actionable data that prompt users to take actions.

3. The said integrated IoT system in claim 1 is applicable for air quality measurement data collection, greenhouse gas emission data collection and hazardous waste material detection to provide user remote monitoring capability and actionable data output.

4. The said integrated IoT system in claim 1 is further applicable for hydrocarbon detection in soil and seawater;

the said integrated IoT system is applicable in oil drilling, monitoring pipelines and oil refinery management to provide remote monitoring with actionable results with a platform of integrated communications.

5. The said integrated IoT system platform in claim 1 is applicable in Fisheries and Aquaculture management.

6. The said integrated IoT system platform in claim 1 is further applicable in Semiconductor Fabrication Plant and Chemical Plant to monitor and provide actionable data to reduce equipment downtime and improve productivity.

7. The said integrated IoT system platform in claim 1 is further applicable in Oceanography, atmospheric and environmental monitoring for global warming to provide useful and actionable data.

8. The said integrated IoT system platform in claim 1 is also applicable to detect earthquake and tsunami where it sends smart alerts to mobile phones to minimize death and destruction.

9. The said integrated IoT system platform in claim 1 further covers monitoring old infrastructure such as:

bridges, electric grid, dams, roads, tunnels, airports to determine structural integrity and maintenance ahead of time.

10. The said integrated IoT system platform in claim 1 is further applicable use in building monitoring and factory management.

11. The said integrated IoT system platform in claim 1 is further applicable in data center management.

12. The said integrated IoT system platform in claim 1 is further applicable in inventory management and inventory tracking.

13. The said integrated IoT system platform in claim 1 is further applicable in logistics and supply chain management.