Mesh networks open IOT’s rich last mile data seams for mining

By Kishore Jethanandani

Mesh networks (or the alternative star topology networks connecting devices to routers) afford the mining of data in IOT’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.

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 rarely tapped 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 ten 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 blow-ups. 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.

We spoke to Rob Chandhok, the President and Chief Operating Officer at San Francisco-based Helium Systems Incorporated, 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,” Rob Chandhok explained to us.

The touchstone of Helium’s technology is 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,” Rob Chandhok told us. 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.

Configurable sensors help to tailor a solution to the outcome desired. Vaccine potency is the greatest if the temperature stays in the 2-8 degrees centigrade (35.6F-46.4 F). By contrast, cell cultures are rendered useless, and thousands of dollars lost, if the temperature falls out in the range of 37 degrees (plus or minus 0.5) centigrade.

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

The roster of solutions expands as Helium learns 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, Rob 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. “Nurses are unable to keep pace as patients are moved after short intervals before and after operations,” Rob Chandhok explained.

For a field site application, we 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,” Ganesh Sivaraman told us. 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,” Erin O’Bannon told us. “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,” Erin O’Bannon explained.

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 homeowners. Analytics companies can potentially create duplicative infrastructure left to themselves. We 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 blockchain-based contracts,” Shilpi Kumar, Product Development, told us. “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,” Shilpi Kumar revealed.

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.

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Customers can now see that the early CRM technologies had a modest objective of accumulating transaction data. The truth is that the “irrational optimism” about CRM clouded judgments in the 1990s. The “irrational pessimism” that ensued missed the promise of CRM, i.e., the ground had been prepared for decision support solutions including predictive analytics.



Customers can now see that the early CRM technologies had a modest objective of accumulating transaction data. The truth is that the “irrational optimism” about CRM clouded judgments in the 1990s. The “irrational pessimism” that ensued missed the promise of CRM, i.e., the ground had been prepared for decision support solutions including predictive analytics.