Data processing: database and file management or data structures – Database design – Data structure types
Reexamination Certificate
2001-07-03
2004-03-09
Mizrahi, Diane D. (Department: 2175)
Data processing: database and file management or data structures
Database design
Data structure types
Reexamination Certificate
active
06704742
ABSTRACT:
CROSS-REFERENCE TO RELATED APPLICATIONS
Not applicable.
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT
Not applicable.
BACKGROUND OF THE INVENTION
The field of the invention is database management and more specifically methods and apparatus for automatically configuring a database as a function of the ways in which the data in the database is used.
While the present invention may be used in many different high information volume industries, in order to simplify this explanation, the invention will be described in the context of the building or enterprise automation (EA) industry. In addition, while the invention may be used with many different enterprises, the invention will be described in the context of an exemplary first enterprise owned by a first company and including seven separate campuses in different geographic regions where each campus includes a plurality of separate buildings and each building includes several thousand different environment condition sensors. Specifically, a first campus includes twenty separate buildings and each building includes two thousand separate sensors. In addition, it will be assumed that the first campus is in a location where the campus may receive its energy from either of three different utilities.
Moreover, separate sub-sections or parts of an enterprise will be referred to generally as units. For example, a sensor may be referred to as a unit. Similarly, a room (including many sensors), a floor of a building, a building, a campus, etc., may each be referred to as a unit. Other units may include a geographic area, a section of the enterprise related to a specific customer, a section of the enterprise serviced by a specific vendor, etc. Furthermore, while any of several different processors, work stations, etc. may perform the inventive functions, the invention will be described in the context of an exemplary system including a single database having a database processor and a single work station for accessing the database and manipulating data therein and also for receiving commands from a system administrator and providing reports and other data to the administrator. Here the station is used to interface with the processor and it will be assumed that the database processor performs essentially all data and database manipulation functions.
Furthermore, the term “data segment” will be used to refer to a subset of data values stored in a database where the sub-set may include anywhere from one to a theoretically infinite number of data values. In addition, while there are hundreds of functions that may be performed on data to generate data segment, unless indicated otherwise, the present invention will be described in the context of total and average power functions in order to simplify this explanation.
While there are many different costs associated with running any type of facility, recent energy shortages have made energy an ever increasingly important consideration in running many facilities. Fueled in part by increasing energy costs, facility administrators are now routinely charged with reducing energy, operating, and maintenance costs.
One way to reduce energy costs is to modify the ways in which energy is used in a facility and, where inefficiencies are identified, to modify the facility or energy use patterns to address the inefficiencies. For instance, in the case of the first campus described above, if off peak energy is delivered at a lower rate than on peak energy, first campus buildings may be cooled down in the morning during an off peak period prior to employees arriving to reduce energy costs. As another instance, cool air flow rate may be altered if a cooling system is more efficient than anticipated.
One other way to reduce energy costs is to identify errors in utility charges and receive credits. To this end, it is known that utilities monitor energy usage by collecting use data at periodic demand intervals. For instance, an exemplary demand interval may be every 15 minutes so that a utility collects a reading every 15 minutes. At the end of a billing cycle, the utility bases its energy charges on the demand interval readings. By measuring energy more regularly (e.g., every minute) and taking the average over the utility's demand cycle, it has been found that often the demand interval readings are higher than actual average energy usage over the demand interval period. When confronted with such information utilities have routinely given credits to customers. In many cases the credits have amounted to as much as several percent (e.g., 10%) of the total energy bill during some billing cycles.
Yet one other way to reduce energy costs is to “shop” for energy by comparing energy rates from various utilities in an area. Thus, for example, in the case of the first campus described above, the campus administrator may select an energy provider from any of the three different utilities in the area.
In addition to reducing energy costs, facility administrators are also routinely charged with reducing maintenance costs and increasing up time of facility equipment. In order to reduce maintenance costs equipment can be diagnostically monitored to estimate when preventive maintenance should be performed. To this end, by trending operating characteristics of facility equipment (e.g., an HVAC system) and comparing the trending results with known failure patterns for similar equipment, impending problems with the equipment can be identified and addressed.
While several ways to reduce operating and maintenance costs have been described above, there are many other ways to reduce costs that a facility administrator can choose from and the examples above are not meant to be exhaustive.
One common characteristic of each of the cost saving processes described above is that, for each process to be most effective, each process requires collection of facility operating data. For instance, in the case of modifying energy use patterns, massive amounts of data have to be collected in order to identify inefficient energy patterns and other enterprise inefficiencies. Similarly, in order to identify utility mis-charges, energy readings have to be gathered every minute for a facility. In the case of the company described above that has many buildings on many campuses, the information that must be gathered is enormous. In the case of maintenance trending the amount data to be collected is massive.
Even the seemingly simple task of shopping around for the best deal on energy costs requires facility data collection and analysis. At first blush one would think that the best deal on energy costs could be determined by simply comparing utility rates. Unfortunately, often rates are different during different times of day and during different times of year. Complicating matters further, facility energy use is often very different at different times of day and different times of year. Thus, to determine the most cost effective utility form which to purchase power, historical energy use rates and times have to be collected and used as a proverbial “glimpse” into the future. For instance, knowing energy use patterns over a previous year period, an administrator can apply different utility rate schedules for the coming year to determine likely cost per utility and then select the least expensive option for a facility or enterprise.
Thus, the EA industry is not unlike other industries where, over the last several decades, computer workstations and related electronic devices have evolved to the point where they are now useful and, in many cases indispensable, tools needed for running businesses. Workstations and related devices have made it possible to collect massive amounts of information in a fraction of the time that would be required without the use of such tools.
Despite advancements in database management, related technological advances such as inexpensive sensors, standard network protocols (i.e., RMON, SNMP, etc.) and the ability to quickly and relatively inexpensively network data collecting devices together have, in some cases,
Blaha Michael R.
Huth William A.
Ignasiak John C.
Michals Steven A.
Schuster Tobin J.
Foley & Lardner
Johnson Controls Technology Company
Mizrahi Diane D.
Mofiz Apu M
LandOfFree
Database management method and apparatus does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Database management method and apparatus, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Database management method and apparatus will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3203019