Project

4D Lean Business Nervous System: Innervation

Goal: We see a convergence of several disruptive technologies; 802.11, IEEE 1451 standard plug-and-play sensors, smart sensors, sensor webs, smart dust, web services, storage networks, and hyper-exponential scaling on both memory and processors, to cheaply “innervate" and move down the price point of traditional SCADA implementations by an order-of-magnitude. This innervation is required before machine learning and intelligence can be embedded. We seek funding to create a digital, adaptive “4D Lean Business Nervous System” built on the innervating technologies above

Updates
0 new
1
Recommendations
0 new
0
Followers
0 new
2
Reads
0 new
51

Project log

Roger N. Anderson
added a research item
Berlin, Paris, and Tokyo, to name just a few, are consumed in producing the comfort and safety of tenants in high-rise office and apartment buildings. In turn, forty percent of energy costs in these buildings go to maintaining and operating the HVAC air conditioning and heating systems. High-Rise city buildings are obligated to provide comfortable spaces for the tenants that they house. The operation of these skyscrapers is in great need of energy optimization. Large buildings also occupy a very important information space, affecting the decisions of local governments and power-grid companies, as well as providing necessary services of security, water, and sewage, as well as power and digital infrastructures such as fast and uniformly available Internet for all. As the world has moved into the big-data Computer Aided Learning Machine (CALM) era, Artificial Intelligence and Machine Learning (AI/ML) are utilized by us to optimize and build more secure and efficient energy systems. The need is not only for large urban buildings, but also for university campuses, military bases, hospitals, industrial and manufacturing facilities. But energy efficiency must be accompanied by improved productivity that sustains clean, comfortable and safe operating environments. We a patented AI/ML system-of-systems approach that requires that each building, campus, etc. must be treated as if it were like an organism, with data sensors providing innervation throughout all critical components. A central brain is then needed to provide the identification of problems, evaluation of possible solutions, and prioritization of actions-all in real time (see Refs for our CALM Book and Patent links). In the even bigger picture, converting our cities to electric transportation systems is needed to fight climate-change. That requires conversion from gasoline and diesel service stations to electric recharge sites and e-parking garages. That, in turn, requires the electric grid to deliver more and more electricity with ever more efficiently to cities in environmentally and carbon neutral ways. That, in turn, requires massive, renewable electricity sources such as wind and solar farms with huge battery backup for when the wind does not blow and the sun does not shine, as well as new intelligent transmission lines. That, in turn, requires integration with distributed generation and storage facilities, such as photovoltaics on every rooftop and Universal Power Supply (UPS) type batteries in every garage. That, in turn, requires integration of the electric grid with other vital infrastructures like transportation, gas, water and sewage because electric pumps are critical to all these systems. That, in turn, requires all cities to modernize the entirety of their infrastructures, and all that must be integrated into a smart AI/ML system-of-systems with enough controls, monitors, intelligence, and above all physical and cyber security. That, in turn, requires all this to be placed underground so that the larger and more frequent hurricanes and wild-fires accompanying Climate-change do not take out the electricity so that the power must never go out. My lab has been working for 40 years on this CALM AI/ML computational learning system-of-systems for energy optimization of all kinds. First and foremost, CALM's AI/ML methods must be used throughout, effectively combining many sources of information to derive predictions of outcomes from past, present and future performance forecasts.
Roger N. Anderson
added 2 research items
The shift in production monitoring of drainage provides maximum profits if 3D Seismic is repeated over time in a reservoir. Impact on the Oil Industry.
Roger N. Anderson
added 2 research items
A Calculus of Value based on Ubiquitous Silicon Inspired by Nature We foresee every value-based decision to use this calculus of value under uncertainty -- even a pump can know its real options and its synergies (covariance) with other devices. • The silicon will be there and cheap with ample compute power to implement this at the smallest levels. • Real Options well be extended to Dynamic Real Options – i.e. the silicon will dream up new options. – The dream phase of the adaptive control algorithms uses simulation and genetic algorithms to come up with new options. – Deep ties with Quantum Mechanics and variational principles in physics • This may sound like fantasy, but it is all very realizable and a large body of work already developed in separate areas. Need to put it all together
Albert Boulanger
added an update
See this research proposal
and this presentation
Presentation vetting-9-10-02
 
Albert Boulanger
added 3 research items
The purpose of Computer Aided Lean Management (CALM) is to enable operational innovation through the deployment of software algorithms. Lean management is a methodology for efficient enforcement of process rigor and discipline in order to dramatically cut costs and improve operations of an enterprise (see http://leanenergy.ldeo.columbia.edu/ogj). This software development will also reduce operating risk, enhance customer service and reliability, and increase the assurance that a new design introduced to the "market" will be effective. CALM is software-controlled lean systems integration that drives breakthroughs in cost and risk reduction. Operational innovation within an energy organization will be enabled through the integrated deployment of three major software systems that we call the Integrated System Model (ISM):  Product modeling-High resolution model of physical infrastructure.  Business process modeling-Capturing detailed process and work flow information in order to track and measure performance on a daily basis with a goal of optimizing these processes.  Machine learning system-Diagnostic analysis of historical and operational data captured in existing data as well as from Product model and Business Process model outputs to predict and/or prioritize required operations and maintenance of an energy company's business. CALM is a methodology for running a business based on the common sense approach of measuring the results of actions taken and using those measurements in an experimental way to design new processes that drive out inefficiencies. In the ISM we will have models of the business where alternatives can be explored to find the innovations required to improve the company's performance. The ISM will provide the tools needed to "see" the competitive landscape or environment the company operates in. Some the feedback to improve performance will be provided by the machine learning tools being developed in this project. The company will need these tools and will need to adopt CALM in order to become more adaptive and therefore better able to perform successfully in the future as the "business we are in" changes.
Albert Boulanger
added 2 research items
We see a convergence of several disruptive technologies; 802.11, IEEE 1451 standard plug-and-play sensors, smart sensors, sensor webs, smart dust, web services, storage networks, and hyper-exponential scaling on both memory and processors, to cheaply “innervate" and move down the price point of traditional SCADA implementations by an order-of-magnitude. This innervation is required before machine learning and intelligence can be embedded. We seek funding to create a digital, adaptive “4D Lean Business Nervous System” built on the innervating technologies above. Our 4D Lean Business Nervous System will incorporate adaptive algorithms and Lean Engineering processes at their most fundamental level. Each widget, such as a motor, will then understand (via cheap embedded silicon) its impact on business choices -- via fine-grained real options, using extensions of IEEE 1451 TEDS electronic spec sheets to include its business side. The cheap silicon associated with the widgets will make up the distributed smarts of the digital nervous system. The attached silicon is also used for last-mile connectivity via 802.11 Wi-Fi and later Ultra Wideband. The 4D Lean Business Nervous System uses web services at its lowest level with a grid computing system on top to host the real options, adaptive reinforcement learning, dynamic programming, and genetic algorithm learning cycles. It will incorporate storage area network technology to distribute the traditional SCADA data historians' functionality for tag (time series data) storage to the critical devices themselves. Adaptive learning is a fundamental property of our innervated infrastructure. It is designed to be built-in so that it becomes "free” and ubiquitous. In other words, learning is designed into the system at the most fundamental level. Metrics are kept of all actions so that continuous improvement becomes the norm. We believe that innervation with the 4D Lean Business Nervous System is a key to creating agile distributed infrastructure security.
We see a convergence of several disruptive technologies; 802.11, IEEE 1451 standard plug-and-play sensors, smart sensors, sensor webs, smart dust, web services, storage networks, and hyper-exponential scaling on both memory and processors, to cheaply “innervate" and move down the price point of traditional SCADA implementations by an order-of-magnitude. This innervation is required before machine learning and intelligence can be embedded. We seek funding to create a digital, adaptive “4D Lean Business Nervous System” built on the innervating technologies above.
Albert Boulanger
added a project goal
We see a convergence of several disruptive technologies; 802.11, IEEE 1451 standard plug-and-play sensors, smart sensors, sensor webs, smart dust, web services, storage networks, and hyper-exponential scaling on both memory and processors, to cheaply “innervate" and move down the price point of traditional SCADA implementations by an order-of-magnitude. This innervation is required before machine learning and intelligence can be embedded. We seek funding to create a digital, adaptive “4D Lean Business Nervous System” built on the innervating technologies above