US 12,033,751 B2
Systems and methods for operations and incident management
Alister Garry Leong, Singapore (SG); Qasim Rasul Khan, Singapore (SG); Paul Keng Teoh, Singapore (SG); Daniel Mark Alcantara, Singapore (SG); Nigel Koh Chong Hoe, Singapore (SG); and Alexey Pisarev, Singapore (SG)
Assigned to SOL-X Pte. Ltd., Singapore (SG)
Filed by SOL-X Pte. Ltd., Singapore (SG)
Filed on Dec. 3, 2020, as Appl. No. 17/110,320.
Claims priority of provisional application 62/943,995, filed on Dec. 5, 2019.
Prior Publication US 2021/0174952 A1, Jun. 10, 2021
Int. Cl. G16H 40/63 (2018.01); G06N 20/00 (2019.01); H04L 67/52 (2022.01); H04Q 9/00 (2006.01)
CPC G16H 40/63 (2018.01) [G06N 20/00 (2019.01); H04L 67/52 (2022.05); H04Q 9/00 (2013.01)] 28 Claims
OG exemplary drawing
 
1. A method for managing safety and risk in a remote workplace comprising:
(a) collecting, via a local network deployed to the workplace that is on a movable object, data stream from one or more sensors and a user device, wherein a geo-location of the local network is detected and wherein a data transmission scheme between the local network and a cloud server is determined based at least in part on the geo-location, and wherein the data transmission scheme specifies which portion of the data stream to be transmitted from the local network to the cloud server, a data center, a cloud database and a third party entity, when and at what frequency to transmit the portion of the data stream;
(b) transmitting, via the local network, the data stream to an edge computing device located within the workplace, wherein the data stream is stored in a database local to the workplace;
(c) processing the data stream as input by one or more trained predictive models running on the edge computing device, and outputting (i) a predicted hazardous condition associated with a work zone within the workplace and (ii) a predicted health condition of a user associated with the user device, wherein the one or more predictive models are trained and developed using machine learning algorithm at an entity remote from the workplace; and
(d) generating a dynamic geofencing area associated with the work zone, wherein the dynamic geofencing area is generated by adjusting a boundary of the dynamic geofencing area base at least in part on the predicted hazardous condition, and determining a permitted duration for the user to be in the dynamic geofencing area based at least in part on the predicted health condition.