Scalable Portable Sensory and Yield Expert System for BioMass Monitoring and Production

• US 20120003728A1
• Filed: 07/01/2010
• Published: 01/05/2012
• Est. Priority Date: 07/01/2010
• Status: Abandoned Application

• Current Assignee: Mark Allen Lanoue
• Original Assignee: Mark Allen Lanoue
• Inventors: Lanoue, Mark Allen, Kaliczak, Janek
• Application Number:
  US12/828,362
• Publication Number:
  US 20120003728A1
• Time in Patent Office: Days
• US Class Current: 435/288.7
• CPC Class Codes: C12M 21/02 Photobioreactors culturing algae A01G33/00, A01H4/001, C12N1/12
• CPC Class Codes: C12M 41/48 Automatic or computerized control automatic analysis G01N35/00
• CPC Class Codes: C12M 43/02 Bioreactors or fermenters combined with devices for liquid fuel extraction; Biorefineries
• CPC Class Codes: C12M 43/06 Photobioreactors combined with devices or plants for gas production different from a bioreactor of fermenter
• CPC Class Codes: Y02E 50/30 Fuel from waste, e.g. synthetic alcohol or diesel

Abstract

The invention relates to the field of algae biofuel production, in particular to methods and means of physical action on biological structures of photosynthesing microorganisms, phototrophic algae in particular. The invention can be used for obtaining biofuel from algae, as well as for the pharmaceutical, cosmetic and foodstuff industries. In the process of the method implementation radiation of cultivated solution of photosynthesizing microorganisms/phototrophical algae is carried out by the action of electromagnetic waves of a selected intensity. Stimulation of increasing photosynthesizing microorganisms/phototrophical algae biomass is obtained by the interaction of electromagnetic wave and biological cell. Irradiation of cultivated solution of photosynthesizing microorganisms/phototrophical algae is performed by electromagnetic waves originating from specified sensor mechanisms mounted about the acrylic or plastic-based stackable tubular bioreactor. Nutrients, carbon dioxide and other dissolved substances are monitored by this sensor system which is controlled by a supercomputer-based control mechanism.

Claims

1. A system for optimizing plant growth in a liquid environment within an enclosed growth chamber, comprising:

illumination means for controlling spatial, temporal and spectral characteristics of illumination surrounding the growth chamber, said illumination means comprising an array of individually actuable light sources, made up of organic light emitting diodes (OLED), is a light-emitting diode (LED) whose emissive electroluminescent layer is composed of a film of organic compounds that emit light when an electric current passes through it. This layer of organic semiconductor material is formed between two electrodes, where at least one of the electrodes is transparent. Just like passive-matrix LCD versus active-matrix LCD, OLEDs can be categorized into passive-matrix and active-matrix displays. Active-matrix OLEDs (AMOLED) require a thin-film transistor backplane to switch the individual pixel on or off, and can make higher resolution and larger size displays possible. The individual pixels then can be turned on as a group to produce light in the visible spectrum and containing frequencies that are particular to maximizing the group of the biomass material through photosynthesis. This array would surround the group tube containment vessel whether the tubes were vertical or horizontal configurations and supply lighting in the required frequencies needed to maximize plant growth and to minimize the power comsumption of said system;

this would be in tandem with other lighting support such as centered mercury and other prior art lighting for agricultural based systems. The system can also supply specific on and off spectral frequencies, a continuous rolling mode switching the spectral frequencies into a dynamic moving configuration. This control allows for specific control over the circadian day night rhythm to increase plant growth. The lighting system is arranged as a blanket around the growth tubes within the system and having differing spectral wavelengths, and means for individual control and modulation of said light sources within each growth tube of said said system So that a series of growth tubes would create a cell of tubes either in a vertical or horizinal configuration. The biomass detection means comprising at least one imaging device which can identify and map location and quantity of plants in a growth medium within the growth cell configuration. The plant stress detection means for acquiring spatially distributed image data which characterize plant vigor and stress within the growth chamber, according to said growth tube cell patterns, said plant stress detection means comprising at least one imaging device selected from the group consisting of multispectral imagers, and hyperspectral imagers;

environmental monitoring means for monitoring a plurality of environmental parameters that affect plant growth in a liquid within a growth chamber;

environmental control means for controlling each of said environmental parameters; and

an expert system coupled to receive data generated by said biomass detecting means, said plant stress detection means, said imager and said environmental monitoring means, and coupled to control said illumination means and said environmental control means;

wherein said expert system contains a knowledge base that includes heuristic information, a plant database containing cultivation diagnostic and spectral information for plants growing within the growth chamber, and plant biomass and stress detection algorithms; and

said expert system is trained to regulate said illumination, environmental parameters and the motors pumps and valves that control movement of plant material, nutrients and gases within the growth tube chambers as a plurality of the whole. This expert system is trained so as to achieve optimized uniform plant growth with minimized consumption of energy and materials, to diagnose deviations from optimal growth conditions, and to determine and implement remedial actions by adjustment of said illumination, dissolved gases and environmental parameters. Said expert control system would repeat indefinitely the expert control cycle to remove mature plants and materials from said environment to a predetermined process holding area and renew the expert process by bringing in startup plant growth materials and recycled and new nutrients and gases to repeat the process again until maturity was again retained and to repeat this process. The system contains growth modules which we have defined as a plurality of grow tubes in cell, and multiples of these cells in the system. Each growth cell contains a number of growth tubes arranged in either a vertical or a horizontal configuration for a plurality of all. Each cell with its growth module tubes has sensing control modules to monitor the biomass materials, gasses, nutrients, lighting, flow and maturity of the biomass. The biomass and the additional materials circulate within the plurality of cells until mature as defined by the expert control system. At maturity the biomass and all materials are taken to the extraction system which separates the algae fuel, also called algal fuel, algaeoleum or second-generation biofuel, is a biofuel which is derived from algae. The expert system which controls this entire process is connected through a wireless mesh network throughout the entire system which terminates at the Expert system which is trained to operate the entire production process

3. The system according to claim 1 and claim 2 will take the discarded materials after the separation of algae lipid fuel oil. Anaerobic digestion is a series of processes in which microorganisms break down biodegradable material in the absence of oxygen, used for industrial or domestic purposes to manage waste and/or to release energy. The result of this process is methane gas.

4. The system according to claim 1 will take the ALGAE OIL LIPIDS produced by the separation as described in claims 2 and 3 and use it directly in engines modified to use it directly without refining.

5. The system according to claim 1 will take the ALGAE OIL LIPIDS produced by the separation as described in claims 2 and 3 and use it as feedstock for the system oil refinery. There it can be transformed into fuel by hydro cracking (which breaks big molecules into smaller ones using hydrogen) or hydrogenation (which adds hydrogen to molecules). These methods can produce aviation fuel, gasoline, diesel, and propane. One type of algae, Botryococcus braunii produces a different type of oil, known as a triterpene, which is transformed into alkanes by a different process. The system is designed to take advantage of many different processes that are extremely small and portable in nature and would be controlled by the expert system through the Wireless mesh network (WMN).

6. The system according to claim 1 will take a plurality of sensors, spectral sensors, motor controllers, pump controllers, electro mechanical controllers and network these devices with the expert system. The Wireless mesh network (WMN) is a communications network made up of a plurality of radio nodes organized in a mesh topology that connects a plurality of the system growth cell modules . The system wireless mesh network consists of mesh clients, mesh routers and gateways. The mesh clients are often laptops, cell phones and other wireless devices while the mesh routers forward traffic to and from the gateways which may but need not connect to the expert system and internet. The coverage area of the radio nodes working as a single network is sometimes called a mesh cloud. Access to this mesh cloud is dependent on the radio nodes working in harmony with each other to create a radio network. A mesh network is reliable and offers redundancy for network communications in this network. When one node can no longer operate, the rest of the nodes can still communicate with each other, directly or through one or more intermediate nodes. Failures of components in this system will then be noticed quickly. FIG. 1 illustrates how the wireless mesh networks would be distributed to monitor plant growth, movement of nutrients, gases, control of valves, pumps in the system. The expert system can then be trained to self form and self heal by sounding an alarm when failures do occur for maintenance and replacement of failed devices. Wireless mesh networks can be implemented with various wireless technology including 802.11, 802.16, cellular technologies or combinations of more than one type. A wireless mesh network can be seen as a special type of wireless ad-hoc network. It is often assumed that all nodes in a wireless mesh network are immobile but this need not be so. The mesh routers may be highly mobile. Often the mesh routers are not limited in terms of resources compared to other nodes in the network and thus can be exploited to perform more resource intensive functions. In this way, the wireless mesh network(WMN) differs from an ad-hoc network since all of these nodes are often constrained by resources. The plurality of components of this fuel production system depend on the WMN to control and direct a plurality of time dependent functions and actions for full process under Expert System control.

7. The system according to claim 1 will take a plurality of the methane gas produced in the anaerobic digestion process and use this methane gas in electrical generation equipment to supply electrical power to a plurality of the system and devices requiring electrical power

8. The system according to claim 1, further comprising a growth zone monitoring imager for identifying and mapping the growth of plants within the liquid medium contained in the chamber, according to said expert grid cell pattern.

9. The system according to claim 1, further comprising a network communications link between said expert system and a remote terminal which includes a machine/human interface, whereby a remotely situated supervisory individual may communicate with and override said expert system and provide control functions outside of the expert system. This supervisory individual could also retrain the Expert System with new values.

10. The system according to claim 6, wherein said interface includes multiple display means for displaying data from said detection and monitoring means, and diagnostic and environmental control determinations from said expert system to multiple repeaters within the system, even including remote wireless machine/human interface.

11. The system according to claim 6, wherein said environmental control means comprises delivery and control systems for each of said environmental parameters.

12. The system according to claim 5, wherein said environmental parameters include at least one parameter selected from the group consisting of temperature, plant nutrients, carbon dioxide and other gases, water and nutrients and comparable data by which to compare to. And volumetric measurements to assess the movement of the biomass through said array cell structure

13. The system according to claim 6, wherein the expert system adjusts said delivery and control systems based on a comparison of data from said monitoring and detection systems with optimum conditions stored in the plant database, using a heuristic technique that can be modified by the machine/human interface.

14. The system according to claim 1, wherein said expert system controls operation of said illumination means in response to said spatially distributed image data from said plant stress detection means to achieve a spatial, spectral and temporal distribution of illumination within the growth chamber that optimizes uniform plant growth, maximizes yield, and minimizes power consumption would be compared to the plant life maturity profile stored in the expert system and may be modified through the machine/human interface.

15. The system according to claim 1, wherein:

periods of light and dark within the chamber are specific and the periods are controlled by the expert system and may also be modified through the machine/human interface.

16. The system according to claim 8, wherein said expert system controls said illumination and spectral frequency such that illumination is distributed to cells that contain biomass.

17. The system according to claim 10, wherein said expert system controls illumination on a cell by cell basis within said grid cell pattern, such that illumination is concentrated on growth tubes clustered into a cells within which plant stress is detected;

also parameters of maturation.

18. The system according to claim 14, 15, and 16, wherein said light sources comprise an array blanket surrounding a plurality of growth tubes in a collection called a cell, each lighting blanket of organic light emitting diodes, which emit light at differing wavelengths on each pixel in the (OLED) array blanket, and which are distributed within each cell of the grid cell pattern according to a predetermined distribution.

19. The system according to claim 14, 15, 16, 17 wherein, when light is being distributed to biomass within a particular cell, the light energy is modulated according to a predetermined temporal pattern controlled by the Expert System.

20. The system according to claim 14, 15, 16, 17, wherein said predetermined temporal pattern includes modulating said light energy between first and second intensity levels at a predetermined frequency.

21. The system according to claim 14, 15, 16, 17 wherein said first intensity is zero and said second intensity has a fixed predetermined value.

22. The system according to claim 14, wherein said predetermined frequency is selected from a range between 200 and 1100 nm and through the machine/human interface as well as upgraded with further ranges as needed in the future such as Thermal and Middle (IR) wave ranges up to and including a spectral frequency of up to 2500 nanometers

24. The system according to claim 6, further comprising a communications link between said expert system and a remote terminal which includes a machine/human interface, whereby a remotely situated individual may communicate with and override said expert system.

25. The system according to claim 6, wherein said interface includes display means for displaying data from said detection and monitoring means, and diagnostic and environmental control determinations from said expert system.

26. The system according to claim 17, wherein said expert system controls said illumination in response to said spatially distributed crop growth information to achieve a spatial, spectral and temporal distribution of illumination within the growth chamber that optimizes plant growth, maximizes yield and minimizes power consumption.

27. The system according to claim 20, wherein, when light is being distributed to biomass within a particular cell, and the light is modulated according to a predetermined temporal pattern.

28. The system according to claim 21, wherein said predetermined pattern includes modulating said light energy at a predetermined frequency.

29. The system according to claim 22, the intensity has a fixed predetermined value.

33. The system according to claim 26, wherein said illumination means comprises an expert system that receives crop growth and chemical information from said imaging means, and controls conditions within each cell of said grid cell pattern in response to said crop growth information, and expert system. Expert system has to do with sensory open and closed loop secure systems, monitoring, sensory systems, decision making, and database operation.

34. The system according to claim 27, wherein said expert system controls said illumination on a cell by cell basis, such that illumination is distributed only to those cells that contain biomass.

35. The system according to claim 28, wherein said expert system controls said illumination such that illumination is concentrated on cells within which plant stress and delayed maturation is detected.

36. The system according to claim 28, wherein said light sources comprise an array of organic light emitting diodes, which emit light at pre determined wavelengths, and which are distributed within each cell of the grid cell pattern according to a predetermined distribution.

37. The system according to claim 28, wherein, when light is being distributed to biomass within a particular cell, the light frequency is set according to a predetermined temporal pattern.

41. The system according to claim 1, wherein data from said biomass detection means is used for empirical biomass estimation.

42. The system according to claim 1 with all system components will operate in multimode configurations for all transport systems and all fixed based systems, single story, multistory, above or below ground.

2. The system according to claim one separates the algae fuel organism into lipids, or oil and the remaining discarded materials, the algae'"'"'s carbohydrate content can be fermented through anaerobic digestion into bioethanol and biobutanol or the plurality of the discarded materials can be placed into a bioreactor to produce methane for fueling the electrical generation system that supplies power to the entire system. The volumetric use of this discarded material to make one or the other of the manufactured materials in this process will be controlled by the expert system.

23. A system for achieving optimized plant growth, comprising:

a liquid growth chamber consisting of cells which contain a number of growth tubes either in horizontal or vertical configuration which is sealed off from an ambient environment;

imaging means for acquiring and monitoring spatially spectral distributed plant growth information within said growth chamber, said imaging means comprising at least one device selected from the group of many cells consisting of a multispectral imager, and a hyperspectral imager;

environmental monitoring means for acquiring and monitoring data regarding environmental conditions within said liquid growth chamber;

illumination and environmental control means for controlling illumination and environmental conditions in said growth chamber; and

an expert system that is coupled to said imaging means and said environmental means, said expert system being trained to analyze and evaluate crop growth conditions within the liquid growth chamber using a heuristic method, and to control said illumination and environmental control means to achieve optimized biomass crop growth and minimum consumption of energy and nutrients.

30. The system according to claim 23, wherein said predetermined frequency is selected from a range between 200 and 1100 nm with future enhancements up to 2500 na[n]ometers.

32. The system according to claim 23, wherein:

said illumination means comprises a matrix of individually operable light sources that corresponds to said grid cell pattern; and

said light sources include sources that emit light at a plurality of preselected wavelengths.

39. The system according to claim 32, wherein said first intensity is zero and said second intensity has a fixed predetermined value.

40. The system according to claim 32, wherein said predetermined frequency is selected from a range nominally between 200 and 1100 nm.

31. A system for controlling crop growth within a growth area, said system comprising:

imaging means for monitoring spatially distributed crop growth information according to a predetermined grid cell pattern within said growth area; and

illumination means for controlling spatial, temporal and spectral distribution of illumination within individual cells of said grid cell pattern in response to said crop growth and chemical information.

38. The system according to claim 31, wherein said predetermined pattern includes modulating said light energy at a predetermined frequency or modulating the frequencies separately or in concert with a predetermined frequency.