Big Data and the Internet of Things

Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea

Piggybacking on an Autonomous Hauler: Business Models Enabling a System-of-Systems Approach to Mapping an Underground Mine

With ever-increasing productivity targets in mining operations, there is a growing interest in mining automation. In future mines, remote-controlled and autonomous haulers will operate underground guided by LiDAR sensors. We envision reusing LiDAR measurements to maintain accurate mine maps that would contribute to both safety and productivity. Extrapolating from a pilot project on reliable wireless communication in Boliden's Kankberg mine, we propose establishing a system-of-systems (SoS) with LIDAR-equipped haulers and existing mapping solutions as constituent systems. SoS requirements engineering inevitably adds a political layer, as independent actors are stakeholders both on the system and SoS levels. We present four SoS scenarios representing different business models, discussing how development and operations could be distributed among Boliden and external stakeholders, e.g., the vehicle suppliers, the hauling company, and the developers of the mapping software. Based on eight key variation points, we compare the four scenarios from both technical and business perspectives. Finally, we validate our findings in a seminar with participants from the relevant stakeholders. We conclude that to determine which scenario is the most promising for Boliden, trade-offs regarding control, costs, risks, and innovation must be carefully evaluated.Comment: Preprint of industry track paper accepted for the 25th IEEE International Conference on Requirements Engineering (RE'17

Regulating Data as Property: A New Construct for Moving Forward

The global community urgently needs precise, clear rules that define ownership of data and express the attendant rights to license, transfer, use, modify, and destroy digital information assets. In response, this article proposes a new approach for regulating data as an entirely new class of property. Recently, European and Asian public officials and industries have called for data ownership principles to be developed, above and beyond current privacy and data protection laws. In addition, official policy guidances and legal proposals have been published that offer to accelerate realization of a property rights structure for digital information. But how can ownership of digital information be achieved? How can those rights be transferred and enforced? Those calls for data ownership emphasize the impact of ownership on the automotive industry and the vast quantities of operational data which smart automobiles and self-driving vehicles will produce. We looked at how, if at all, the issue was being considered in consumer-facing statements addressing the data being collected by their vehicles. To formulate our proposal, we also considered continued advances in scientific research, quantum mechanics, and quantum computing which confirm that information in any digital or electronic medium is, and always has been, physical, tangible matter. Yet, to date, data regulation has sought to adapt legal constructs for “intangible” intellectual property or to express a series of permissions and constraints tied to specific classifications of data (such as personally identifiable information). We examined legal reforms that were recently approved by the United Nations Commission on International Trade Law to enable transactions involving electronic transferable records, as well as prior reforms adopted in the United States Uniform Commercial Code and Federal law to enable similar transactions involving digital records that were, historically, physical assets (such as promissory notes or chattel paper). Finally, we surveyed prior academic scholarship in the U.S. and Europe to determine if the physical attributes of digital data had been previously considered in the vigorous debates on how to regulate personal information or the extent, if at all, that the solutions developed for transferable records had been considered for larger classes of digital assets. Based on the preceding, we propose that regulation of digital information assets, and clear concepts of ownership, can be built on existing legal constructs that have enabled electronic commercial practices. We propose a property rules construct that clearly defines a right to own digital information arises upon creation (whether by keystroke or machine), and suggest when and how that right attaches to specific data though the exercise of technological controls. This construct will enable faster, better adaptations of new rules for the ever-evolving portfolio of data assets being created around the world. This approach will also create more predictable, scalable, and extensible mechanisms for regulating data and is consistent with, and may improve the exercise and enforcement of, rights regarding personal information. We conclude by highlighting existing technologies and their potential to support this construct and begin an inventory of the steps necessary to further proceed with this process

Launching the Grand Challenges for Ocean Conservation

The ten most pressing Grand Challenges in Oceans Conservation were identified at the Oceans Big Think and described in a detailed working document:A Blue Revolution for Oceans: Reengineering Aquaculture for SustainabilityEnding and Recovering from Marine DebrisTransparency and Traceability from Sea to Shore:  Ending OverfishingProtecting Critical Ocean Habitats: New Tools for Marine ProtectionEngineering Ecological Resilience in Near Shore and Coastal AreasReducing the Ecological Footprint of Fishing through Smarter GearArresting the Alien Invasion: Combating Invasive SpeciesCombatting the Effects of Ocean AcidificationEnding Marine Wildlife TraffickingReviving Dead Zones: Combating Ocean Deoxygenation and Nutrient Runof

Towards design elements to represent business models for cyber physical systems

Cyber-physical systems turn products into connected devices that enable interaction among individu-als, organizations, and other objects. They find application in areas such as healthcare and automo-tive, enabling new value propositions created by multiple players for a shared customer. Despite the perceived business potential, practitioners in primarily physical industries struggle to analyze and design value creation mechanisms for cyber-physical systems. The prevailing business model concep-tualizations follow a mono-organizational logic and are unable to express hybrid and interactive val-ue creation. To close this gap, we apply a design science research approach to develop and evaluate a taxonomy of design elements to represent business models for cyber-physical systems. Through an analysis of 21 use cases of value creation mechanisms in the automotive industry, we identify the de-sign elements adopted in practice; we then validate the identified design elements via 13 interviews and a workshop with our target users, obtaining a final taxonomy comprising 23 design elements. We improve the expressive power of business model conceptualizations by identifying specific roles, con-trol points, and value exchanges in a network of players, representing hybrid and interactive value creation

Internet of Robotic Things Intelligent Connectivity and Platforms

The Internet of Things (IoT) and Industrial IoT (IIoT) have developed rapidly in the past few years, as both the Internet and “things” have evolved significantly. “Things” now range from simple Radio Frequency Identification (RFID) devices to smart wireless sensors, intelligent wireless sensors and actuators, robotic things, and autonomous vehicles operating in consumer, business, and industrial environments. The emergence of “intelligent things” (static or mobile) in collaborative autonomous fleets requires new architectures, connectivity paradigms, trustworthiness frameworks, and platforms for the integration of applications across different business and industrial domains. These new applications accelerate the development of autonomous system design paradigms and the proliferation of the Internet of Robotic Things (IoRT). In IoRT, collaborative robotic things can communicate with other things, learn autonomously, interact safely with the environment, humans and other things, and gain qualities like self-maintenance, self-awareness, self-healing, and fail-operational behavior. IoRT applications can make use of the individual, collaborative, and collective intelligence of robotic things, as well as information from the infrastructure and operating context to plan, implement and accomplish tasks under different environmental conditions and uncertainties. The continuous, real-time interaction with the environment makes perception, location, communication, cognition, computation, connectivity, propulsion, and integration of federated IoRT and digital platforms important components of new-generation IoRT applications. This paper reviews the taxonomy of the IoRT, emphasizing the IoRT intelligent connectivity, architectures, interoperability, and trustworthiness framework, and surveys the technologies that enable the application of the IoRT across different domains to perform missions more efficiently, productively, and completely. The aim is to provide a novel perspective on the IoRT that involves communication among robotic things and humans and highlights the convergence of several technologies and interactions between different taxonomies used in the literature.publishedVersio