Modularization for Product Competitiveness - Analysis of Modularization in the Digital Camera Industry -

Focusing on the digital camera industry with high Japanese competitiveness in IT industry, entrants are analyzed in detail as to how growth was achieved after the period of market introduction and particularly from the view of modularization and platform strategies of leading companies. As a result, the involvement of indicators such as product production, development lead-time, and price with the strategies of modularization and platform was analyzed.Product Development, Modularity, Product Platform, Vertical Integration, Product Strategy

When Handsets Became Smart

The main cause of the intra industry value migration is that the base of competition has shifted from product performance to flexibility, differentiation and speed which in this industry means ecosystem, brand and time-to-market. The asymmetric business models and the two-sided platforms have proven to be a cause of inter industry value migration. This is a natural cause of their nature, since resources is spent in one end and value is absorbed in the other, and if these parts operate in different industries, inter industry value migration has to happen. Our value flow framework has proven to be a useful tool to identify, measure and evaluate a value flow, regardless of the industry level it occurs on

Security industry standards – a research agenda

The security industry has traditionally been highly fragmented and vendors have opted for proprietary standards that induce customer lockin. Several factors – including absence of network effects, end-user heterogeneity and low barriers of entry – have contributed to the dearth of standards. The shift to digital product platforms did not initially change the structural dynamics that inhibit standards within the industry. However, as the security industry breaks away from vertical integration and is coming to resemble the modular IT industry, the need for increased interoperability has become a critical issue

Use of Single Board Computers as Smart Sensors in the Manufacturing Industry

The continuously growing presence of cyber-physical systems in the industry, especially in the field of processes automation and control, represents the paradigm of the so called fourth industrial revolution, in which the systems are smarter, faster and more optimized by means of artificial intelligence, control systems and sensors networks. The presence of ICT and automation systems guarantees energy and other resources efficiency along the whole value chain of industrial processes. Especially important is the case of the smart sensors, in which a conventional sensor is equipped with interfacing methodologies for signal processing and decision making. In this article the capabilities of using a single board computer as a smart sensor are explored.Postprint (published version

A Vision for the future

For the past 40 years, computer scientists and engineers have been building technology that has allowed machine vision to be used in high value applications from factory automation to Mars rovers. However, until now the availability of computational power has limited the application of these technologies to niches with a strong enough need to overcome the cost and power hurdles. This is changing rapidly as the computational means have now become available to bring computer vision to mass market applications in mobile phones, tablets, wearables, drones and robots enabling brand new user-experiences within the cost, power and volumetric constraints of mobile platforms

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

Analyzing the Impact of Spatio-Temporal Sensor Resolution on Player Experience in Augmented Reality Games

Along with automating everyday tasks of human life, smartphones have become one of the most popular devices to play video games on due to their interactivity. Smartphones are embedded with various sensors which enhance their ability to adopt new new interaction techniques for video games. These integrated sen- sors, such as motion sensors or location sensors, make the device able to adopt new interaction techniques that enhance usability. However, despite their mobility and embedded sensor capacity, smartphones are limited in processing power and display area compared to desktop computer consoles. When it comes to evaluat- ing Player Experience (PX), players might not have as compelling an experience because the rich graphics environments that a desktop computer can provide are absent on a smartphone. A plausible alternative in this regard can be substituting the virtual game world with a real world game board, perceived through the device camera by rendering the digital artifacts over the camera view. This technology is widely known as Augmented Reality (AR). Smartphone sensors (e.g. GPS, accelerometer, gyro-meter, compass) have enhanced the capability for deploying Augmented Reality technology. AR has been applied to a large number of smartphone games including shooters, casual games, or puzzles. Because AR play environments are viewed through the camera, rendering the digital artifacts consistently and accurately is crucial because the digital characters need to move with respect to sensed orientation, then the accelerometer and gyroscope need to provide su ciently accurate and precise readings to make the game playable. In particular, determining the pose of the camera in space is vital as the appropriate angle to view the rendered digital characters are determined by the pose of the camera. This defines how well the players will be able interact with the digital game characters. Depending in the Quality of Service (QoS) of these sensors, the Player Experience (PX) may vary as the rendering of digital characters are affected by noisy sensors causing a loss of registration. Confronting such problem while developing AR games is di cult in general as it requires creating wide variety of game types, narratives, input modalities as well as user-testing. Moreover, current AR games developers do not have any specific guidelines for developing AR games, and concrete guidelines outlining the tradeoffs between QoS and PX for different genres and interaction techniques are required. My dissertation provides a complete view (a taxonomy) of the spatio-temporal sensor resolution depen- dency of the existing AR games. Four user experiments have been conducted and one experiment is proposed to validate the taxonomy and demonstrate the differential impact of sensor noise on gameplay of different genres of AR games in different aspect of PX. This analysis is performed in the context of a novel instru- mentation technology, which allows the controlled manipulation of QoS on position and orientation sensors. The experimental outcome demonstrated how the QoS of input sensor noise impacts the PX differently while playing AR game of different genre and the key elements creating this differential impact are - the input modality, narrative and game mechanics. Later, concrete guidelines are derived to regulate the sensor QoS as complete set of instructions to develop different genres or AR games