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University of Washington: upcoming Internet accessible lecture on #IoT #Wearables Technology

Next Thursday at UW CSE or view remotely:

Computer Science and Engineering

SPEAKER:   David Kotz, Dartmouth College

TITLE:     Amulet: An Energy-Efficient, Multi-Application Wearable

DATE:      Thursday, December 1, 2016
TIME:      3:30pm
PLACE:     EEB-105
HOST:      Tadayoshi Kohno

Wearable technology enables a range of exciting new applications in
health, commerce, and beyond. For many important applications, wearables
must have battery life measured in weeks or months, not hours and days as
in most current devices. Our vision of wearable platforms aims for long
battery life but with the flexibility and security to support multiple
applications. To achieve long battery life with a workload comprising apps
from multiple developers, these platforms must have robust mechanisms for
app isolation and developer tools for optimizing resource usage.

We introduce the Amulet Platform for constrained wearable devices, which
includes an ultra-low-power hardware architecture and a companion software
framework, including a highly efficient event-driven programming model,
low-power operating system, and developer tools for profiling
ultra-low-power applications at compile time. We present the design and
evaluation of our prototype Amulet hardware and software, and show how the
framework enables developers to write energy-efficient applications. Our
prototype has battery lifetime lasting weeks or even months, depending on
the application, and our interactive resource-profiling tool predicts
battery lifetime within 6-10% of the measured lifetime.

(Featured image: Seattle photo from University of Washington web site at

Continue reading University of Washington: upcoming Internet accessible lecture on #IoT #Wearables Technology

“Enabling High-level Application Development for the Internet of Things” (2015)

Patel, P., & Cassou, D. (2015). Enabling high-level application development for the Internet of Things. Journal of Systems and Software, 103, 62-84.

Retrieved from:

File: 1501.05080.pdf

Paper proposes a software engineering methodology for IoT applications, noting that IoT devices may span a wide area of issues from sensors, wireless connectivity, design techniques, to much more – requiring domain expertise in various phases of the life cycle. The paper then proposes an approach (a model or models described using new high level languages) for the specification, design, development of comprehensive IoT applications. There is a lot of detail in this paper – This is a really interesting paper summarizing the PhD thesis of the first author.

“Privacy of big data in the internet of things era.” (2015)

Perera, C., Ranjan, R., Wang, L., Khan, S. U., & Zomaya, A. Y. (2015). Privacy of big data in the internet of things era. IEEE IT Special Issue Internet of Anything, 6.

File: 1412.8339.pdf

The authors note an objective of IoT is to collect data, and whether that is stored locally or in the cloud, privacy

Notes definition of Big Data in terms of Volume, Variety and Velocity (3Vs), much of the data will be personal, and 60% of Internet users are aware of privacy issues and 85% want more control. But users are willing to give up privacy in exchange for value. Authors suggest that in the future, IoT consumers will be offered two models: (1) give up privacy in exchange for service, or (2) pay a fee to obtain service and retain privacy. Services need to obtain consent but regarding social media privacy policies “most of the users underestimate the authorization given to the third party applications” – in other words, people are giving up more privacy than they realize. Related issue: can users migrate their own data from one service provider to another? And, seldom are we anonymous on the Internet due to modern tracking capabilities. Notes issues with security and lack of updates/patches to IoT devices.

Paper recommends that manufacturers take privacy and security seriously, provide options to enable and disable data collection, limit the transmission of data to the cloud – and then there is the issue of 3rd party application developers and what they build on top of these platforms. While we think of IoT sensors in terms of consumers, in many cases, consumers may not have control, such as the use of IoT sensors in apartments and businesses.

Authors mention several sensors as a service models, including OpenIT, Lab of Things (LoT), Hub of All Things (HAT), Xively and Datacoup.

Use of industrial #IoT leads to efficiencies, customer benefits, and increased profitability

Data collection on industrial equipment usage can lead to improved maintenance scheduling, adding life to equipment and decreasing downtime due to failures:

“Maintenance has always been a cost-driver in industries that rely on expensive equipment in the field (think airlines and major shippers). In these industries, performing field maintenance at just the right time (before the equipment fails but not so early as to scrap excess product life) dramatically impacts profitability and safety. Equipment that must be returned to an MRO station is under even greater scrutiny as this may mean that part of the fleet is inaccessible until the equipment is returned. Machine learning and data gathering are dramatically improving maintenance scheduling, reducing equipment downtime and driving greater profitability.”

Source: 6 Ways Machine Learning is Driving Profits

Movers and Shakers: Kinetic energy harvesting for the Internet of Things. Gorlatova, et al (2014)

Gorlatova, M., Sarik, J., Grebla, G., Cong, M., Kymissis, I., Zussman, G. (2014). Movers and Shakers: Kinetic Energy Harvesting for the Internet of Things.  Columbia University, Electrical Engineering Technical Report #2014-03-27, Mar. 2014.
Retrieved from:
File: 1307.0044.pdf
Examines the use of motion (kinetic energy) harvesting to power IoT devices, specifically, that of people and how they move around during the day. They monitored 40 people for about 200 hours to capture a record of motion, and then developed a model that might be used to estimate the amount of energy that might be collected for powering IoT devices, attached to people (in addition to motion, they also examine the potential use of photovoltaics to collect energy).

Internet of Things. Mulani and Pingle (2016). Paper Summary.

I am reading through a number of published, peer-reviewed papers that are related to the Internet of Things topic. Rather than create a personal annotated bibliography as I go through the papers, I am instead going to try and write paper summaries and comments here on this blog. May as well share what I read!

There is no particular order to these papers. I found them online and saved them in a folder, and am reading them in the order they appear in the folder.


Mulani, T., and Pingle, S.V. (2016) Internet of Things. International Research Journal of Multidisciplinary Studies. March 2016. Retrieved from: File: 270-772-1-PB.pdf

Defines the IoT and then examines issues surrounding IoT, including security, privacy, legal, economic, followed by comments on IoT communications models including peer to peer (device to device), device to cloud, device to gateway and back end data sharing. Concludes that IoT has “technical, social and policy considerations” that need to be examined. But … this paper does not examine them. Reads like a proposal.


#IoT and data collection changes marketing from generic to specific

“Marketing data is evolving: from the generic to the specific; from market trends to individual habits and from historic actions to real-time engagement.

We are moving on from knowing that millennials aged 25 to 30 replace their mobile phone on average every 2.5 years.

We move to knowing that William replaces his Android three months after new major features are established, keeping a general eye on new developments and looking for upgrade deals from his service provider. We also know that Claire pre-orders the new iPhone as soon as the availability date for a new model is announced and has a Google Alert for any mention of Apple iPhones.”

Source: Is big data really the future of marketing? – Marketing Tech News

Good for marketing and sales but the end of anything being considered personal and private. Marketeers and consumers will need to have an open conversation before something bad happens. Of course, collected personal data has never, ever been hacked and dumped into the open. Never. Of course.

“Internet of Everything” might be more accurate than “Internet of Things” #IoT

Some commentators prefer to use the term ‘internet of everything’ rather than ‘internet of things’. This makes sense considering we are talking about everything.

Source: Why marketers need to pay attention to the Internet of Things | Econsultancy

The rapid decline in costs of computing, sensors and connectivity means it is possible to make everything be “smart” (in a sense). What that means – in terms of benefits and drawbacks – is still to be determined. But out of the gate, IoT does seem a bit like IoE. Time will prune the list of applications to those which deliver real value. But in the mean time, yes, it could be the Internet of Everything.