Talking power management utility

• US 9,069,047 B2
• Filed: 06/16/2014
• Issued: 06/30/2015
• Est. Priority Date: 04/08/2011
• Status: Active Grant

• Current Assignee: Dean Figlioli, Madhu Nallabelli
• Original Assignee: Dean Figlioli, Madhu Nallabelli
• Inventors: Nallabelli, Madhu, Figlioli, Dean
• Primary Examiner(s): ALAM, MIRZA F
• Application Number:
  US14/305,307
• Publication Number:
  US 20140292524A1
• Time in Patent Office: 379 Days
• Field of Search: 340/636.1, 340/636, 340/825.44, 340/311.1, 340/663, 340/6.1, 340/335, 340/336.1, 340/636.13, 340/636.19, 340/7.32, 340/7.37, 340/455, 320/106, 320/132, 320/6, 320/48, 320/39, 320/127, 320/136, 320/107, 320/114, 320/134, 320/118, 320/160, 320/124, 320/137, 455/569.2, 455/343, 455/404.1, 455/574, 455/343.2, 455/343.6, 455/550.1, 455/572, 455/573, 455/343.1, 455/343.5, 307/10.7
• US Class Current: 1/1
• CPC Class Codes: G01R 31/371 with remote indication, e.g. on external chargers
• CPC Class Codes: H01M 10/4257 Smart batteries, e.g. electronic circuits inside the housing of the cells or batteries
• CPC Class Codes: H02J 7/0048 Detection of remaining charge capacity or state of charge [SOC]
• CPC Class Codes: H02J 7/005 Detection of state of health [SOH]
• CPC Class Codes: H04W 52/0277 according to available power supply, e.g. switching off when a low battery condition is detected
• CPC Class Codes: Y02D 30/70 in wireless communication networks
• CPC Class Codes: Y02E 60/10 Energy storage using batteries

Abstract

An architecture is presented that provides a computer-implemented system and method for monitoring a remaining battery charge level in a mobile computer cart used in a hospital environment and detecting when said battery charge level is reduced to a selected level. The system comprises a monitoring component that monitors remaining battery charge levels for the mobile computer cart. Further, the monitoring component communicates with a detection component which detects when the battery charge levels of the mobile computer cart are low and/or reach a predetermined threshold level. The system further comprises a trigger component that sends a customizable alert to a user once a low battery charge level and/or a predetermined threshold level has been reached. Furthermore, the system comprises a power component that automatically places the mobile computer cart in detect and protect mode after a predetermined period of time after the alerts are sent.

Claims

1. A computer-implemented method for alerting clinical staff in a hospital environment about a remaining battery charge level on a mobile medical computer cart by monitoring battery charge levels over a period of time via an inverter using a processor coupled to a memory comprising:

monitoring and collecting battery charge level data from the mobile medical computer cart using an inverter, hardware, and a software plugin;

detecting whether battery is weak or strong by analyzing daily battery charging patterns stored in a database over a period of time, using an algorithm;

wherein detecting whether a battery is weak or strong determines at what battery charge threshold level to generate alerts, such that if it is determined that a battery is weak, then the battery charge threshold level is set at a charge level of 50%, and if it is determined that a battery is strong, then the battery charge threshold level is set at a charge level of 40%;

determining a battery charge threshold level to generate alerts by analyzing battery discharge pattern stored in a database over a period of time, using the algorithm;

placing the mobile medical computer cart into a detect and protect mode after a predetermined period of time;

wherein the detect and protect mode is a hybrid power mode where the battery is trickle drained, such that only a small amount of power is required to keep the mobile medical computer cart in a hybrid state;

detecting real-time utilization of the mobile medical computer cart by tracking keyboard and mouse clicks on the mobile medical computer cart; and

triggering voice alerts coupled with visual alerts based on real-time active utilization of the mobile medical computer cart by a user; and

wherein the alert is a user customizable computer-generated human voice message which includes visual and animated characters determined by user actions, such that if the mobile medical computer cart is in use by a user, then only the visual and animated characters are played when the alert is triggered, and if the mobile medical computer cart is not in use by a user, then a computer-generated human voice message and the visual and animated characters are played when the alert is triggered; and

wherein volume of the alert is automatically adjusted to a lower volume during nights as ambient noise is usually lower and the volume of the alert is then automatically adjusted to a higher volume during daylight hours; and

wherein the customizable computer-generated human voice message is customized by a user to various languages, accents, and genders; and

wherein if the mobile medical computer cart is not used for a specified period of time, the mobile medical computer cart is automatically put into the detect and protect mode to save battery usage and is brought to fully functional normal operation with a keyboard or mouse click.

2. The computer-implemented method of claim 1, wherein the monitoring and collecting of the battery charge level data from the mobile medical computer cart comprises utilizing hardware to decode signals coming from the battery or inverter to output battery charge level and trigger the alert.

3. The computer-implemented method of claim 1, wherein the collected battery charge level data is stored in a central database on a server in a hospital network with time stamps for future analysis along with battery charge level data collected from all mobile medical computer carts in a hospital network.

4. The computer-implemented method of claim 2, wherein the hardware comprises a microchip programmed with software to monitor and collect the battery charge level data and store in a database for analysis.

5. The computer-implemented method of claim 1, wherein the software plugin interfaces with the inverter to read, understand and convert the battery charge level data to usable form.

6. The computer-implemented method of claim 1, wherein the software plugin is customized to read and understand various data formats produced by different inverter manufacturers.

7. The computer-implemented system of claim 1, wherein reports run by the algorithm are displayed on a dashboard;

and wherein the dashboard also displays when batteries need to be replaced under two categories “

Replace Soon” and

“

Replace Now”

, utilization of the mobile medical computer cart on a graph in three categories “

Heavily Used”

, “

Moderately Used” and

“

Rarely Used”

, and sends escalation alerts via email or help desk ticket related to hardware failure, battery replacement, low batteries, or no user response for alerts.

8. The computer-implemented method of claim 1, wherein the algorithm analyzes battery data in the database to determine following parameters:

change in battery charge percentage in a given time period, battery charge cycles, time taken to fully charge the battery, time period medical mobile computer cart was plugged in for charging, time period of battery discharge, depth of battery discharge, discharge and charge pattern in a day/week/month/year, load on battery, and number of times battery was depleted to a flat battery in a predetermined period of time.

9. The computer-implemented method of claim 8, wherein the parameters determined are used to determine if the battery is a strong or weak battery.

10. The computer-implemented method of claim 8, wherein the parameters determined are used to calculate threshold charge level for the battery to start alerts and to put the mobile medical computer cart into detect and protect mode.

11. The computer-implemented method of claim 1, wherein the detect and protect mode is decided based on how many times the user is alerted and based on battery discharge level.

12. The computer-implemented method of claim 1, wherein the alert is played at a custom volume for different hospital departments and is scheduled to speak or be muted at specific times.

13. The computer-implemented method of claim 1, wherein the alert is automatically muted from a central console for all mobile medical computer carts in a specific area.

14. The computer-implemented method of claim 4, wherein the software interfaces with call center software to automatically open tickets via HL7, SQL and VBScripts and sends escalation emails, text messages, or pager messages.

15. The computer-implemented method of claim 4, wherein the software analyzes the battery charge level data stored in the database over a period of time and predicts expected life of the battery based on a usage pattern.