WIRELESS OCCUPANCY AND DAY-LIGHT SENSING

• US 20100026479A1
• Filed: 08/02/2007
• Published: 02/04/2010
• Est. Priority Date: 05/24/2007
• Status: Active Grant

• Current Assignee: Clean Energy Management Solutions, LLC (Dominion Harbor Enterprises, LLC)
• Original Assignee: Bao Tran
• Inventors: Tran, Bao
• Granted Patent: US 7,884,727 B2
• Time in Patent Office: Days
• US Class Current: 340/501
• CPC Class Codes: A61B 2560/0412 Low-profile patch shaped housings
• CPC Class Codes: A61B 2560/045 with a separable interface unit, e.g. for communication
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/002 Monitoring the patient using a local or closed circuit, e.g. in a room or building A61B5/0017 takes precedence
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/0059 using light, e.g. diagnosis by transillumination, diascopy, fluorescence A61B5/0093, A61B5/1455, A61B5/02416 and A61B5/0261 take precedence
• CPC Class Codes: A61B 5/02028 Determining haemodynamic parameters not otherwise provided for, e.g. cardiac contractility or left ventricular ejection fraction
• CPC Class Codes: A61B 5/02042 Determining blood loss or bleeding, e.g. during a surgical procedure
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/026 Measuring blood flow A61B3/1233, A61B3/1241 take precedence
• CPC Class Codes: A61B 5/1075 for measuring dimensions by non-invasive methods, e.g. for determining thickness of tissue layer A61B8/0858 takes precedence
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/1113 Local tracking of patients, e.g. in a hospital or private home
• CPC Class Codes: A61B 5/1117 Fall detection
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/1128 using image analysis A61B5/1127 takes precedence
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 5/242 Detecting biomagnetic fields, e.g. magnetic fields produced by bioelectric currents
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/369 : Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/389 : Electromyography [EMG]
• CPC Class Codes: A61B 5/4023 : Evaluating sense of balance
• CPC Class Codes: A61B 5/447 : specially adapted for aiding the prevention of ulcer or pressure sore development, i.e. before the ulcer or sore has developed
• CPC Class Codes: A61B 5/4875 : Hydration status, fluid retention of the body
• CPC Class Codes: A61B 5/4881 : Determining interstitial fluid distribution or content within body tissue measuring analytes in interstitial fluid in-vivo A61B5/1451
• CPC Class Codes: A61B 5/681 : Wristwatch-type devices
• CPC Class Codes: A61B 5/7203 : for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7257 : using Fourier transforms
• CPC Class Codes: A61B 5/726 : using Wavelet transforms
• CPC Class Codes: A61B 5/7264 : Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7267 : involving training the classification device
• CPC Class Codes: A61B 5/7275 : Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/7465 : Arrangements for interactive communication between patient and care services, e.g. by using a telephone network telemetry of measured physiological signal A61B5/0002
• CPC Class Codes: A61B 8/06 : Measuring blood flow measuring volume flow in general G01F, e.g. G01F1/66, G01F1/72; measuring speed of fluids in general G01P5/00
• CPC Class Codes: A61B 8/08 : Detecting organic movements or changes, e.g. tumours, cysts, swellings A61B8/02 - A61B8/06 take precedence
• CPC Class Codes: A61B 8/565 : involving data transmission via a network
• CPC Class Codes: G16H 10/60 : for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 : ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 40/63 : for local operation

Abstract

A system to control energy consumption in a room uses a wireless mesh network that allows for continuous connections and reconfiguration around blocked paths by hopping from node to node until a connection can be established, the mesh network including one or more wireless area network transceivers adapted to communicate data with the wireless mesh network, the transceiver detecting motion by analyzing reflected wireless signal strength.

Claims

1. A system to control energy consumption in a room, comprising:

a wireless data transceiver, said transceiver detecting motion by analyzing reflected wireless signal strength; and

an appliance coupled to the transceiver, the appliance being activated or deactivated in response to sensed motion in the room based on the reflected wireless signal strength.

2. The system of claim 1, comprising a recognizer coupled to the transceiver including one of:

a Hidden Markov Model (HMM) recognizer, a dynamic time warp (DTW) recognizer, a neural network, a fuzzy logic engine, a Bayesian network.

3. The system of claim 2, wherein the recognizer monitors one or more personally identifiable signatures including Doppler signature of a person'"'"'s chest.

4. The system of claim 1, wherein the transceiver identifies one person from another based on a Doppler heart rate signature.

5. The system of claim 1, comprising a sound transducer coupled to the wireless transceiver to communicate audio over a telephone network through the mesh network.

6. The system of claim 5, comprising a call center coupled to the transceiver to provide a human response.

7. The system of claim 1, comprising an in-door positioning system coupled to one or more mesh network appliances to provide location information.

8. The system of claim 1, wherein the transceiver comprises a Multiple Input Multiple Output (MIMO) transceiver coupled to a plurality of MIMO antennas, wherein the MIMO transceiver comprises a Doppler radar.

9. The system of claim 1, comprising a smart meter coupled to the appliance, wherein the smart meter includes bi-directional communication, power measurement and management capability, software-controllable disconnect switch, and communication over low voltage power line.

10. The system of claim 1, comprising a remote processor that can remotely turn power on or off for the appliance, read usage information from a meter, detect a service outage, detect the unauthorized use of electricity, change the maximum amount of electricity that the appliance can demand, and remotely change the meters billing plan from credit to prepay as well as from flat-rate to multi-tariff.

11. The system of claim 1, wherein the appliance minimizes operating cost by shifting energy use to an off-peak period in response to utility pricing that varies energy cost by time of day.

12. The system of claim 1, comprising a rechargeable energy reservoir coupled to the appliance, wherein the reservoir is charged during a utility off-peak period and used during a utility peak pricing period.

13. An occupancy sensing system for an area, comprising:

one or more wireless nodes forming a wireless mesh network; and

a wireless transceiver adapted to communicate with the one or more wireless nodes, the wireless transceiver generating a received signal strength indication (RSSI) signal, wireless transceiver including an analyzer to process the RSSI signal to detect occupancy in the area.

14. The system of claim 13, comprising a light emitting diode (LED) coupled to the wireless transceiver, the LED having a first mode to generate light and a second mode to generate a voltage based on ambient light.

15. The system of claim 14, comprising an analog to digital (ADC) converter reading an output from the LED corresponding to ambient light in the area.

16. The system of claim 13, wherein the analyzer identifies one occupant from another based on a Doppler signature.

17. The system of claim 13, wherein the mesh network communicates lighting profiles that incorporate time-based control with occupancy, daylighting, and manual control and wherein the analyzer integrates time-based lighting control with occupancy sensing control.

18. A system, comprising:

a processor;

a transceiver coupled to the processor and communicating an RSSI signal to indicate the presence of one or more persons in a room; and

a light emitting diode (LED) coupled to the processor, the LED generating light in a first mode and sensing room light in a second mode.

19. The system of claim 18, wherein the LED senses sound in a third mode.

20. The system of claim 19, wherein the processor integrates time-based lighting control, sound detection control and occupancy sensing control.

21. The system of claim 18, comprising an energy scavenger coupled to the processor and transceiver and LED to provide power.