Mesh Networks Promise to Tap a Wealth of IoT Data


Mesh networks (or the alternative star topology networks connecting devices to routers) afford the mining of data in the Internet of Thing’s last mile. By interconnecting mobile devices, mesh networks can funnel data from sensors to local gateways or the cloud for analysis and decision-making.

Credit: Pixabay
Credit: Pixabay

Wired and wireless telecom networks do not reach the distant regions or the nooks and crannies for the mining of information-rich seams of data. Mining, oilfields, ocean-going vessels, electricity grids, emergency response sites like wildfires, and agriculture are some of the information-rich data sources that might be tapped rarely for analytics and decision-making in real-time or otherwise.

Where telecom coverage is available, it does not necessarily reach all assets. Data generated by sensors embedded in equipment on factory floors, underground water pipes in cities, or inventory in warehouses cannot readily access cellular or wired networks.

A typical case of a remote field site is that of an oil exploration and production in California with dispersed wells where 10 operators gathered data on tank levels, gas flows, and well-head pressures. Now with a mesh network, operating managers can access this data anywhere and respond to alerts in real-time.

Onsite mesh networks are deployed for microscopic monitoring of equipment to watch for losses such as energy leakages. Refineries are labyrinths of pipes with relief valves to release pressure to avoid blowups. One of them in Singapore had one thousand valves to monitor manually. These valves do not necessarily shut tightly enough, or need maintenance and gases trickle out. Over time, the losses add up to a lot. Acoustic signals can pinpoint otherwise unnoticeable leakages and transmit the data via mesh networks to databases; any deviation from pattern prompts action to stop the losses.

The prospects of on-premise mesh networks adoption have improved with the emergence of smart Bluetooth and beacons. With smart Bluetooth technology, an IP layer is built on top of the data layer for ease of connecting devices. Beacons are publicly available for anyone to use for building networks.

I spoke to Rob Chandhok, the president and chief operating officer at San Francisco-based Helium Systems, to understand his company’s approach to mining the data in IOT’s last mile. Helium’s current solutions target the healthcare industry and in particular its refrigeration and air conditioning equipment. “Hospitals have hundreds of refrigerators to store medicines, which are likely to be damaged if the doors are inadvertently left open,” he explained.

The touchstone of Helium’s technology are its programmable sensors embedded with a choice of scripts capable of rudimentary arithmetic like calculating the difference in temperature between two rooms. As a result, the sensors generate more data than would be possible with the investment in dumb hardware alone. Helium uses star topology for the last mile network connected to the cloud, which hosts a platform for analytical solutions. The entire system is configurable from the sensor to the cloud for generating data for the desired thresholds and alerts or analytical models.

“The architecture is intended to optimize processes across the system,” Chandhok said. He illustrated with an example of the impact of pressure differences; germs are less likely to enter if the internal pressure is higher than the external pressure.

The configurability of the sensors helps to tailor a solution to the outcome desired. Vaccine potency is the greatest if the temperature stays in the 35.6F to 46.4 F range.

In the hospitality industry, the purpose is to improve customer service by keeping temperatures in a comfortable range. Hotel guests do not have to wait until air-conditioning brings temperatures to the desired levels, which vary by region and seasons.

The roster of possible solutions expands as providers learn more about the clients’ problems. In the course of working with customers in hospitals, Helium was made aware of the routine underutilization of beds. Speaking of future plans, Chandhok said, “We can improve the rate of utilization of beds in hospitals with automatic and real-time tracking with infrared sensors.” Currently, nurses manually record the state of occupancy of beds usually with a lag.

For a field site application, I spoke to Weft's Ganesh Sivaraman, director of product management, as well as Erin O’Bannon, director of marketing, about its supply chain solutions. The company uses mesh networks to determine the location and condition of cargo on ships, their expected time of arrival, the inflow of cargo once ships are docked at ports, and the extent of port congestion. “The mesh network brings near real-time visibility to the state of flow of the cargo,” Sivaraman said. However, he clarified that currently its applications do not afford the tracking of cargo at the pallet level and their flow in the supply chain. “We use predictive analytics, using proprietary and third-party data sources, to help clients time the deployment of trucks to pick the cargo with minimal delay,” O’Bannon said. “With visibility, clients can anticipate delays, which lets them plan for alternative routes for trucks to shorten delivery times or switch to air transportation if the gain in time is worth the cost,” she said.

Mesh networks will evolve from vertical to an array of horizontal solutions. Home automation, for example, will likely be linked with fire prevention services and with the connected cars of home owners. Analytics companies can potentially create duplicative infrastructure left to themselves.

I spoke to Shilpi Kumar of Filament, a company specializing in mesh connectivity for industries, to understand how this evolution will shape the architecture of last mile IOT networks.

“Decentralized mesh infrastructure-as-a-service serves the needs of multiple analytics companies with network policies enforced by block chain-based contracts,” Kumar said. “The interlinking of mesh networks with a secure overlay prepares the way of exchanges between devices in an ecosystem such as vehicles paying for parking automatically,” she said.

Mesh networks expand the universe of the Internet of Things by making remote data sources accessible. They also raise the level of granularity of data sources that are nominally reachable with existing networks. As a result, these mesh networks expand the array of opportunities for optimizing business processes.

Kishore Jethanandani, Market Researcher

Kishore Jethanandani's current professional focus is content development and communications of complex subject matter for clients in the technology and financial services industry in the San Francisco Bay and Boston area. His career has evolved from industrial economic research with an accent on policy reform to a business journalist while he was in India to marketing writing and research in the USA. A technology buff and a futurist, he has an instinct for spotting emerging technology and market trends and their likely impact on business strategy and competition.  His personal slogan is "A hedgehog who senses the future". My website can be found at www.futuristlens.com

Mesh Networks Promise to Tap a Wealth of IoT Data

The Internet of Thing's last mile holds rich data seams that can be opened for data mining with mesh networks.

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Re: Interesting
  • 6/19/2016 9:57:55 AM
NO RATINGS

I would think the low hanging fruit of mesh networks may be the remote locations or at least not easily accessible places. Making remote data sources accessible from rural areas and IoT devices attached to even commonplace equipment like hospital refrigerators and equipment monitoring will be the next big thing.

Re: Interesting
  • 6/17/2016 7:58:53 AM
NO RATINGS

,,

Tomsg writes 


I think mesh networks can have a lot of real benefits and this has hit on a few of the big ones. I have seen systems that get to near real time in analysis and then make changes to get better results


 

I can imagine some huge opportunities for mesh networks in public transportation. Managers and supervisors could be linked to various aspects of the current operation and condition of every single bus or railcar (or perhaps those in a specific supervisor's jurisdiction). Analytics could identify problems, or new service conditions, and managers and supervisors might even be able torespond interactively and improve operations.

 

Re: Interesting
  • 6/7/2016 10:32:10 AM
NO RATINGS

I have no idea how you got to be named Data Doctor but that is what is showing up. Sorry, if it is inaccurate

Re: Interesting
  • 6/7/2016 9:11:33 AM
NO RATINGS

I just noticed my status. I am not sure what  data doctor is.

Re: Interesting
  • 6/6/2016 10:26:33 PM
NO RATINGS

Interesting example of the restaurants, Data Doctor. 

Interesting
  • 6/6/2016 5:19:28 PM
NO RATINGS

I think mesh networks can have a lot of real benefits and this has hit on a few of the big ones. I have seen systems that get to near real time in analysis and then make changes to get better results. I saw a restaurant that gauged number of empty seats vs reservations . When things were slow, they advertised specials n a big sugn outside . Asthings filled up, the specials disappeared. They saw a real tangible improvement of their business in this manner.

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