Internet of Things (IoT) Tech Digest - April 2017

Robots and IoT networks 

Researchers from Carnegie Melon University, USA, are investigating the use of wireless sensor networks (WSNs) in agriculture. WSNs can be used for precise irrigation control which would reduce water and nutrient wastage in farming. Software, based on machine learning, would provide the user an overview of the data to generate dynamic plots, create alerts and understanding environmental factors that affect the crops, and provide crop specific irrigation methods. The system also uses an autonomous ground robot that takes surveys of crops at different times of the growing season using a camera, a laser scanner and a multispectral scanner. This information is run through machine learning systems to predict expected fruit yield come harvest time. The team are currently trialling the system. 

Food chain

FoodBlockChain.XYZ is a swiss company that is developing a blockchain-based system for use in the food supply chain. It would use Foodcoin – the company’s own token – between intermediaries eg farmers and food manufacturers. FoodBlockChain.XYZ plans to use a sensor network to monitor food data – such as temperature, composition, origin, safety – throughout the food chain. This should allow everyone on the chain to make informed decisions regarding aspects such as quality and socio-environmental factors. Consumers would also be able to reward ‘good’ farmers by sending them fractions of Foodcoin. The company is currently testing the system with two food companies with the goal of general release in September 2017.  

GM IoT

Bloomberg reports that General Motors’ director of global automation Mark Franks recently said at a conference that around a quarter of the motor company’s 30,000 factory robots have been connected to IoT networks. The telemetry on machine functioning and predictive analysis provided by the connectivity has apparently helped GM to avoid 100 potential failures of machines and assembly robots in the past two years. The IoT systems also help GM to order parts only when it is predicted they will be needed instead of having them sitting in storerooms unused. 

Microsoft 4.0

Microsoft has released an IoT solution for industry utilizing its Azure IoT Hub and Azure Time Series Insights. The solution offers a connected factory preconfigured ecosystem of devices and a six-step framework that the company claims quickly enables organisations to make the leap to ‘Industry 4.0’. The practical six-step framework is broken into three sets of two steps: define and experiment with data sources, connect equipment and gain visibility of manufacturing data, and then expand (make operational changes) and enhance. Azure Time Series Insights offers companies telemetry data and overall equipment effectiveness feedback along with key performance indicators like units produced and energy consumption.

Snow melting system IoT

Holland, Michigan, USA, has a snow melt system that is ripe for connection to the IoT. The snowmelt system works by reusing waste heat from power generation to heat water that circulates through 190 miles of underground piping laid under the roads and pavements of the town. The system pumps 4,700 (17,791.44 litres) US gallons of water per minute at 95 degrees Fahrenheit (35C) that can melt one inch of snow per hour with outside temperatures of -4 degrees Celsius. 
Additions to the system, proposed and prototyped by Realtime AT&T IoT StarterKit challenge winner, Pete Hoffswell, involves connecting the system to an IoT network that would allow monitoring of ground temperature and surface wetness, as well as increase awareness of the system’s strengths and weaknesses. The sensors would be embedded directly into pavements, and onto lamp posts and trees. The prototype IoT system uses AT&T IoT Starter Kit (LTE), AT&T Flow / M2X (to manage the IoT app), PubNub (streams data from sensors to app in real-time as well as sending alert tweets), EON (to visualise the data), rain/snow sensors, temperature sensors. 

Heart and Seoul of IoT

KT, a South Korean telecoms company, and Samsung, an electronics company, have announced the launch of a pilot NB-IoT service in Seoul. The low power network will use 180KHz bandwidth during its two-month trial period. KT will initially be using the network for location tracking services of cargo and goods, with a view to widening the application scope in the future. Samsung has deployed its LTE radio base stations and rolled out its virtualised Cellular IoT Core solution (C-GSN). 

Using Wi-fi signals to monitor movement

A team of scientists at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) in the USA have developed a device that can use wireless signals to measure the walking speed and length stride of multiple people with an accuracy of 95 to 99%. The ‘emitter’ - the size of a small painting - can be placed on a wall to continuously monitor a room. WiGait, as it is called, analyses wireless signals reflected off people’s bodies to specifically measure a person’s steps. The algorithm can distinguish between walking and other activities such as washing the dishes according to the scientists. The projected use of WiGait is to non-intrusively monitor the condition of Parkinson’s sufferers etc. 

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