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| Smart Programmable Wireless Miniature Lamp Module with embedded Fuzzy Logic |
This project involves a smart miniature lamp module with integrated motion sensor, photo sensor, and wireless module
with fuzzy logic algorithms which can be readily programmed to suit custom residential and commercial building needs.
This lamp module fits into most of the commonly used incandescent as well as fluorescent lamp bases for ceilings,
walls, table lamps etc. Other adaptations of this module are also be possible for a variety of lighting fixtures.
Each lamp module can also be programmed to behave as member of a lighting control group. These groups are
defined based on a room’s usage or some other characteristics. For example, lamp modules inside a kitchen are
defined as member of the control group “Kitchen Lighting Control Group”. Lamp modules inside a dining room are
configured to belong to the “Dining Room Lighting Control Group” and so on and so forth. Each module is able to
communicate with any other module in its control group to develop an individual profile of power usage and day light
patterns on a daily, weekly or monthly basis. Algorithms are implemented around certain goals for a particular control
group. Goals can be set to minimize overall lighting consumption in a control group or to maintain a certain luminance
for certain duration of time.
A ‘sink’ is assigned to a number of control groups to communicate to all the lamp modules in those control groups.
Several sinks may be strategically located at various positions in a building. Each sink has a motion sensor, a photo
sensor, a temperature sensor, a wireless module, significant data storage capacity and battery backup. Two or more of
these sinks inside a building then communicate to a control host.
By using the above scheme, we are able to achieve the following:
with fuzzy logic algorithms which can be readily programmed to suit custom residential and commercial building needs.
This lamp module fits into most of the commonly used incandescent as well as fluorescent lamp bases for ceilings,
walls, table lamps etc. Other adaptations of this module are also be possible for a variety of lighting fixtures.
Each lamp module can also be programmed to behave as member of a lighting control group. These groups are
defined based on a room’s usage or some other characteristics. For example, lamp modules inside a kitchen are
defined as member of the control group “Kitchen Lighting Control Group”. Lamp modules inside a dining room are
configured to belong to the “Dining Room Lighting Control Group” and so on and so forth. Each module is able to
communicate with any other module in its control group to develop an individual profile of power usage and day light
patterns on a daily, weekly or monthly basis. Algorithms are implemented around certain goals for a particular control
group. Goals can be set to minimize overall lighting consumption in a control group or to maintain a certain luminance
for certain duration of time.
A ‘sink’ is assigned to a number of control groups to communicate to all the lamp modules in those control groups.
Several sinks may be strategically located at various positions in a building. Each sink has a motion sensor, a photo
sensor, a temperature sensor, a wireless module, significant data storage capacity and battery backup. Two or more of
these sinks inside a building then communicate to a control host.
By using the above scheme, we are able to achieve the following:
- Gather accurate load profiles at various lighting devices in real time.
- Gather daylight patterns in real time.
- Gather activity information for various areas in real time.
- Autonomous control of light intensity through a rules-based decision engine.
- Autonomous control of lighting load based on an area’s requirements.
- Adaptation of the algorithms based on collected data and user feedback.
| Smart Programmable Lamp Module |
| Smart Lamp Module Schematic |
| An example of an area consisting of various lighting control groups, smart lamp modules, sinks and control host |
| N-Dimensional Fuzzy Inferencing Engine |
| Table with 25 Fuzzy Rules |
| Example of membership functions for grading Power Usage and Illuminance in a Lighting Control Group |
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