Author Archives: Lux Research

Beyond the Solution Stack: Data Management for the Internet of Things

When Lux first introduced a framework and taxonomy for approaching the industrial internet of things (IIoT), the focus was on tools and understanding the various parts of the solution stack. The Lux “IIoT Toolbox” provided clients and readers with a structured view of how to turn data from industrial assets, people, and environments into actionable insights to do things like improve operational efficiency, generate new services and revenue streams, and improve employee health and safety. This was an important and valuable baseline for understanding the IoT, and how to properly construct a solution stack.

However, understanding each of the elements in the IoT toolbox was only the first challenge. As clients and readers have started to figure out how to properly construct an IoT solution, the focus now shifts towards refining, optimizing, and future-proofing such a solution. The ensuing challenge here becomes effectively and efficiently managing all of the data generated by the IoT. For this, we propose a data-centric framework and taxonomy to help clients and readers understand the next layer of capabilities, processes, and approaches to properly managing the glut of data being generated within their respective deployments.

In no particular order, the seven core components to this data-centric framework include the following:

  • Data creation (or data generation) references all of the activities related to capturing and contextualizing sensor data. It is more than just recording simple, discrete sensor readings. It is also determining how data is collected, choosing an appropriate sampling frequency, imposing boundaries and limits on the data to filter spurious events, and other activities like manual annotation to further contextualize the data sample.
  • Data security references all of the activities related to isolating data to a discrete audience of authorized individuals, machines, applications, or processes.It is not just the deployment of software and systems such as firewalls, intrusion detection systems (IDS), and antivirus software to keep data isolated and protected. It is also establishing role-based data access, user authentication schema, data encryption, and the utilization of AI and machine learning to continuously monitor for network intrusion or unauthorized data access. It is also the ongoing remediation and patching of systems to ensure data and the surrounding environment remains protected from illicit activity. Many decisions must be made with regard to data security, and they will always appertain to the decisions made with regard to the other components of the data-centric framework.
  • Data transmission references the connectivity and conveyance of data across the entire end-to-end IoT solution stack. It is more than just a singular event of transmitting data from sensor to end device. Data is often transmitted across multiple devices, among multiple locations, using multiple formats or standards, and using varying physical means. Data may be transmitted using short-range technologies, such as Bluetooth or Wi-Fi, or long-range technologies, such as LPWAN or cellular. Data transmission may also take place at varying intervals, and may only involve subsets or summaries of entire data sets. Decisions regarding what to send and how to send it are always unique to the specific end-to-end solution stack.
  • Data cleanliness references the relative signal to noise ratio of the IoT device data being generated. It is a measure of how much useful information was collected, as a proportion of all data collected. Data often requires cleaning and validation prior to being stored and analyzed. Spurious sensor readings, instrumentation failure, transmission failure (leading to incomplete data sets), environmental interference, and other issues can “contaminate” data sets. “Cleaning” data to remove or repair these types of issues helps to ensure the general accuracy and completeness of IoT analytics and insights.
  • Data analytics references all of the activities related to computational processing and understanding of IoT device data. It is the processes involved with examining data sets in order to draw conclusions about the information they contain. Analytics were traditionally administered by human data scientists, but artificial intelligence (AI) and machine learning have expanded the capabilities, speed, and breadth of analytical capabilities of most modern IoT analytics solutions.
  • Data storage references all of the activities related to storing data across the entire end-to-end IoT solution stack. As with data transmission, data may be stored in multiple locations, in multiple formats, and on varying storage media. It is more than simply storing data in a particular digital or physical format. Data may need to be re-formatted in a particular schema (such as JSON or XML), or stored as a file, object or in a database. It may need to be aggregated, annotated, deduplicated, compressed, encrypted, or archived. Many decisions must be made with regard to data storage, and it often depends on other components of the data-centric framework, such as data analytics, transmission, and security.
  • Data sharing references the imparting of data across separate IoT deployments. It may involve an IoT solution ingesting outside, third-party data to provide better internal analytics capabilities. In this scenario, outside data would be used for training of machine learning algorithms, and improving the accuracy of analytics and insights. Data sharing may also involve an IoT solution sending internal data to an outside, third-party entity to enhance collective analytics capabilities. Some platforms even enable the monetization and sale of internal data, which opens the possibility of generating new revenue streams.

We plan to explore each of these components in greater detail in upcoming journals. For each topic, we will discuss traditional approaches, key innovations, and some specific applications demonstrating the importance of each. Readers should continue to follow the discussion surrounding effectively and efficiently managing all of the data generated by their own respective IoTs.

Stop Looking for the Fountain of Youth: Invest Instead in Healthy Aging in Place

In recent years, the eternal topic of aging and the concern that people have around this natural process has gained increased attention from the media, entrepreneurs, and scientists. This topic was even included in the HBO TV series “Silicon Valley,” where one of the characters undergoes a blood transfusion from a younger individual to replace their “old” blood with new blood full of youthful energy. While, this might only seem like a work of fiction, a startup called Ambrosia is actually offering these “young blood” transfusions at $8,000 each. In fact, during the past five years, a number of companies and projects have emerged intending to battle the process of aging. For instance, an Alphabet subsidiary, called Calico, intends to use biotechnology to understand aging-related health conditions and develop “interventions that enable people to lead longer and healthier lives.” Continue reading

A Sticky Situation: Demand for Novel Adhesives Exists, but Products Slow to Materialize

The use of adhesives has long been intertwined with our everyday lives, with one of the earliest use cases dating to circa 200,000 years ago in the form of tar-hafted stone tools. Today, adhesives are ubiquitous – found in packaging, automobile, aerospace, construction, medical, and consumer industries – and dominated by companies like Henkel, 3M, Huntsman, DowDuPont, Sika, H.B. Fuller, BASF, and Pidilite. Continue reading

Apple’s New iPhone X Points Smartphone Technology in a New Direction

This month’s iPhone X launch comes a full decade after the iPhone’s original debut and harkens back to its first release in 2007. Like the original, the X is priced much higher ($999 for 64GB and $1,149 for the 256 GB model) than the average phone available today; the first iPhone was originally priced at $399, while most phones at the time were $199. The release of X is also similar to the original, with its limited availability due to manufacturing constraints and its certain role as a status symbol. Continue reading

Robotic Cleaning Systems for Photovoltaics Is the First Step to a New Balance-of-Systems Package

Utility-scale solar systems are increasingly becoming competitive with conventional energy sources as tariffs continue to drop, largely as a result of sinking module costs. Under these market conditions, the U.S. Department of Energy SunShot Initiative – a support organization for the commercialization of solar technologies – announced it has reached its 2020 goal of an average cost for utility-scale systems at $0.06/kWh three years early. As such, SunShot has promised $62 million to support concentrated solar power systems and $20 million for supporting power electronics. The SunShot Initiative’s goal is to improve grid reliability and resilience as photovoltaic systems continue to become interconnected, but there is still significant understanding needed to improve the lifetime reliability of photovoltaic systems themselves. Continue reading

Changi Airport’s Adoption of AR-Enabled Smart Glasses and the State of Enterprise Wearables Today

Singapore’s Changi airport recently announced that it will be implementing the use of AR-enabled Vuzix M300 smart glasses for its ground handling crew members. The cameras on the smart glasses scan a QR code on cargo and baggage containers and display relevant information such as weight, loading sequence, and allocated position within the aircraft. The smart glasses will also allow for easier audio communication between crew members, as well as streamline the work of the control center, who will have full access to the video feed of each pair of smart glasses. Continue reading

Volkwagen’s Electrification Roadmap Now Includes 80 Plug-Ins and 150 GWh of Batteries by 2025

In May 2017, Volkswagen (VW) brand CEO Herbert Diess claimed that VW will surpass Tesla to be the world leader in electric mobility by 2025 – an aggressive target, but coming from a company with the resources to achieve it. At the International Motor Show in Frankfurt, Germany, VW CEO Matthias Müller announced Volkswagen’s Roadmap E, committing those resources to a strategy that aims to transform one of the world’s largest OEMs. This roadmap is made up of several key initiatives: Continue reading

Energy Drives Defensive Innovation in the Steel Industry

In recent years, there has been rapid innovation in the development and processing of structural metals, particularly for high-performance alloys. Lux has covered high-end metals innovation extensively, much of which has been driven by advances in 3D printing, simulation and modeling software, materials informatics, and novel approaches to alloy design, such as high-entropy alloys. As a result, the development, production, and processing of high-performance metals continues to get cheaper as quality improves. Continue reading

A Taxonomy for Innovation in Sleep

Last month, Fitbit unveiled its new smart watch, the Fitbit Iconic. The company plans to utilize the device’s new blood oxygen saturation sensors (relative SpO2) for sleep apnea diagnosis. For Fitbit, the new functionality in the Iconic is a natural progression from its previous work; but from a broader perspective, Fitbit’s recent innovation represents yet another data point of a bigger story: sleep is hot. Today, sleep has already become widely accepted as a primary pillar of wellness (even the Apple Health Kit will vouch for this), and sleep tracking has become ubiquitous in consumer wellness solutions; yet recently we’ve witnessed an uptick in innovation of sleep-specific solutions. Below, we use Lux’s Tech Signal to uncover spikes in interest in sleep innovation, which primarily took off in 2013:

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What Venture Funding and Unicorn Status Mean for Startup Strategies in Additive Manufacturing

While many venture-backed 3D printing companies approach fundraising with careful consideration towards overvaluation and future “down round” risks, two high profile 3D printing companies have taken these risks to a new level. Carbon and Desktop Metal have raised nine-figure funding rounds, ultimately attaining unicorn status (at least a $1 billion valuation for a private company), which helps separate them as up and coming leaders in additive manufacturing. With this level of fundraising comes inherent risks; the technology must live up to its potential across multiple applications to achieve expected growth. This technical risk is partially mitigated by extensive financial support for product development, and partnership opportunities through industry interest in such well-funded startups. Continue reading