FUGITIVE GAS DETECTION SYSTEM
A fugitive gas detection system is provided. The system includes a cloud service, a plurality of reach-based components, a plurality of wireless gas sensors. The reach-based components comprise backhauls and gateways. The wireless gas sensors are acted as nodes to acquire sensor data in a local mesh network and the nodes are connected to the cloud service through the reach-based components, one node can transmit the sensor data to other sensor nodes of the local mesh network. The system measures flammable gas levels with speed, economy and accuracy.
1 . A fugitive gas detection system, comprising,
a cloud service;
a plurality of reach-based components;
a plurality of wireless gas sensors operating as nodes to acquire sensor data;
wherein the nodes are connected to the cloud service through the reach-based components.
2 . The system of claim 1 , wherein the reach-based components comprise backhauls and gateways.
3 . The system of claim 1 , wherein the nodes are deployed near a monitoring field to form a local mesh network through self-organization, nodes can transmit the sensor data to other sensor nodes of the local mesh network.
4 . The system of claim 1 , wherein the gas sensor is a MEMS based multigas sensor.
5 . The system of claim 4 , wherein the MEMS based multigas sensor includes a plurality of probes to detect special qualities of a gas.
6 . The system of claim 5 , wherein the special qualities of the measured gas are recorded by a radar chart, the MEMS based multigas sensor detects the species and concentration of the gas using the radar chart.
7 . The system of claim 4 , wherein the gas is selected from the group consisting of methane, ethane, propane, butane, acetone, and methanol.
8 . The system of claim 4 , wherein the gas a mixture of any two or more species of methane, ethane, propane, butane and acetone.
9 . The system of claim 3 , wherein comprising each of the nodes includes an autonomous local controller.
10 . The system of claim 1 , wherein the nodes further comprising sensors selected from level sensors, vibration sensors, state of valve sensors and pressure transducers.
11 . The system of claim 1 , further comprising an on-board GPS on each node.
12 . The system of claim 1 , further comprising an Industrial Internet of Things (IIoT) platform.
13 . The system of claim 12 , wherein the system operates risk analysis using the sensors to determine a probability of risk for a given industrial site.
14 . The system of claim 12 , wherein the system runs in a local controller mode in which each node is stand-alone and runs singularly and autonomously.
15 . The system of claim 12 , wherein the system runs in a few nodes controller mode in which a potentially small number of nodes are operating autonomously and in a mesh network.
16 . The system of claim 12 , wherein the system runs in a local mesh with local gateway mode in which local collection sensors and/or controllers are monitored by a local gateway.
17 . The system of claim 12 , wherein the system runs in an autonomous mode in which local decision-making is included in the IIoT platform.
18 . The system of claim 12 , wherein the system runs in a data analytics mode in which cloud-based data is analyzed by taking current and historical data to evaluate systemic releases, calculate long term risk performance and behavior.
19 . The system of claim 12 , wherein the system runs edge computing algorithms allowing for local decisions to be made at the sensors.
20 . The system of claim 19 , wherein the local decisions are selected from the group consisting of valve closure upon gas detection, valve closure after receiving kill signal from other nodes.