System Bits: July 12

Simplifying sensor network interactions
Given that the IoT consists of millions of sensing devices in buildings, vehicles and elsewhere that deliver reams of data online, and involves so many different kinds of data, sources and communication modes that its myriad information streams can be onerous to acquire and process, scientists at Georgia Tech Research Institute have developed a flexible, generic data-fusion software that simplifies interacting with sensor networks.

The FUSE software is meant to be a framework to standardize the diverse IoT world, and its API lets users capture, store, annotate and transform any data coming from Internet-connected sources.

The researchers stressed that the IoT has always been something of a Tower of Babel, because it gathers data from everywhere – from the latest smart-building microcontrollers and driver-assist vehicles to legacy sensors installed for years, and traditionally, people wanting to utilize IoT information have had to examine the attributes of each individual sensor and then write custom software on an ad-hoc basis to handle it.

GTRI researchers (l-r) Heyward Adams, Andrew Hardin and Greg Bishop examine Internet of Things devices whose output can be integrated using GTRI’s new FUSE software. (Source: Georgia Tech)

Before FUSE, the team said a typical IoT task could require several manual steps but FUSE allows a task that used to involve a week or two, and complete in 10 or 15 minutes by providing a standard way of communicating in the unstandardized world of IoT.

To build their framework, the researchers developed advanced algorithms for handling the many different source types, communication modes and data types coming in over the internet. They also devised methods for managing interactions among data sources that use varying and unpredictable data rates.

FUSE makes extensive use of the generic representational state transfer (REST) data capability; referred to as RESTful, this widely used Internet standard supports the framework’s ability to receive and transmit divergent data streams. FUSE is designed to be massively distributable: using load-balancing techniques, the service can spread IOT workloads across entire computer clusters but it can also operate on small and inexpensive microcontrollers of the type increasingly found in buildings and vehicles performing a variety of smart sensing tasks.

Smartphone motion sensor fingerprinting poses privacy threat
According to ECE ILLINOIS Professor Nikita Borisov, your smartphone can already detect your movement, it can sense if you’ve rotated it to take a landscape photo, and how you’ve tilted it to play a game, and this technology can also be exploited by advertisers with motion sensor fingerprinting.

In a new paper, Borisov and colleagues describe a possible method to track smartphone users by analyzing the device’s unique motion sensing data.

The team explained that conventional workarounds like private browsing and clearing cookies would no longer be effective against this new method of mobile tracking, because it relies upon data collected about the physical device itself.

They also explored two counter-measures and how they impacted the user experience in web applications. Both a previously proposed obfuscation technique and a newly developed quantization technique were able to drastically reduce fingerprinting accuracy without significantly impacting the utility of the sensors in web applications in a user study.

Portable sensor detects trace amounts of gluten in food
Aiming to create a peace of mind at mealtime, MIT spinout Nima has developed a portable gluten sensor to allow diners — such as those with celiac disease or gluten intolerances that may experience adverse reactions even from trace amounts of their allergen — to determine if their food is safe to eat.

To use the Nima sensor, a new device that can detect gluten, diners put a pea-sized sample of food or liquid into a disposable capsule, and insert the capsule into the device, which mixes the food into a solution that detects gluten. In two to three minutes, a digital display appears on the sensor, indicating if the food sample does or doesn’t contain gluten.
(Source: MIT and Nima)

Nima’s sensor, also called Nima, is a 3-inch-tall triangular device with disposable capsules. Diners put a sample of food — about the size of a pea — or liquid into the capsule, screw on the top, and insert the capsule into the device, which mixes the food into a solution that detects gluten. In two to three minutes, a digital display appears on the sensor, indicating if the food sample does or doesn’t contain gluten.

Nima can sense gluten at 20 parts per million (ppm) or more, the maximum concentration for “gluten-free” foods as determined by the U.S. Food and Drug Administration. 

Next year, Nima plans to release two new sensors, one for peanuts and one for dairy, the company added.

Other Research Bits This Week
Power/Performance Bits
Manufacturing Bits