Autonomous proximity awareness of bluetooth devices

This paper focuses on designing autonomous device discovery algorithms for Bluetooth networks. We first extend the conventional asymmetric Bluetooth link model to three point-to-point symmetric link models. Their performances are compared analytically. To achieve proximity awareness among a group of Bluetooth devices, three control information exchanging methods are also proposed. Combining with the three link models, this gives 9 possible variants of autonomous device discovery algorithm. A comprehensive comparative study based on these 9 variants is then carried out using Bluehoc simulator. © 2005 IEEE.published_or_final_versio

Bluetooth-base Worm Modeling And Simulation

Bluetooth is one of the most popular technologies in the world in the new century. Meanwhile it attracts attackers to develop new worm and malicious code attacking Bluetooth wireless network. So far the growth of mobile malicious code is very fast and they have become a great potential threat to our society. In this thesis, we study Bluetooth worm in Mobile Wireless Network. Firstly we investigate the Bluetooth technology and several previously appeared Bluetooth worms, e.g. Caribe , Comwar , and we find the infection cycle of a Bluetooth worm. Next, we develop a new simulator, Bluetooth Worm simulator (BTWS), which simulates Bluetooth worm\u27 behaviors in Mobile wireless networks. Through analyzing the result, we find i) In ideal environment the mobility of Bluetooth device can improve the worm\u27s propagation speed, but combining mobility and inquiry time issue would cause a Bluetooth worm to slow down its propagation under certain situation. ii) The number of initially infected Bluetooth devices mostly affects the beginning propagation speed of a worm, and energy issue can be ignored because the new technology can let Bluetooth device keeping work for a long time. iii) Co-channel interference and setting up monitoring system in public place can improve the security of Bluetooth wireless network

Recent advances in industrial wireless sensor networks towards efficient management in IoT

With the accelerated development of Internet-of- Things (IoT), wireless sensor networks (WSN) are gaining importance in the continued advancement of information and communication technologies, and have been connected and integrated with Internet in vast industrial applications. However, given the fact that most wireless sensor devices are resource constrained and operate on batteries, the communication overhead and power consumption are therefore important issues for wireless sensor networks design. In order to efficiently manage these wireless sensor devices in a unified manner, the industrial authorities should be able to provide a network infrastructure supporting various WSN applications and services that facilitate the management of sensor-equipped real-world entities. This paper presents an overview of industrial ecosystem, technical architecture, industrial device management standards and our latest research activity in developing a WSN management system. The key approach to enable efficient and reliable management of WSN within such an infrastructure is a cross layer design of lightweight and cloud-based RESTful web service

Navigating Complexity in an Internet of Things Era: A Case Study of Entrepreneurial Leadership in a Silicon Valley IoT Startup

Research into the inner-workings of high-tech startups in the field of leadership within the United States is needed. The accelerating impact of technology on society is clear. The Internet of Things (IoT) is a primary technology of an emergent era, the Fourth Industrial Revolution (Industry 4.0). Silicon Valley startups germinate many of these Industry 4.0 IoT technologies. The current understanding of leadership in IoT startups is often based on media reports. recounting villains and heroes. This is not that. This is a qualitative, normative case study based on the researcher’s insider status at an IoT startup. Insider case study research into leadership of this type is sparse. Based on a review of the literature, multiple one-on-one interviews were conducted with leaders in an IoT startup. An additional 12 interviews were conducted with leaders in the IoT startup field. This study asks: What does it take to lead an IoT startup in Silicon Valley? The data supported the use of Goffman’s (1959b) dramaturgy as an analytical tool for leadership. The leadership at IoT Inc. took on prescribed roles in formal and informal settings. Bourdieu’s (2020) social capital, habitus, and field concepts are also supported for analyzing IoT startups. The individuals at IoT Inc. used social capital, and exhibited habitus based on experiences and expertise while interacting with the IoT field. Chia’s (2013) process-orientation and application of knowledge types like techne, metis, and phronesis is supported. Leaders in the case study exhibited complexity-based leadership when pursuing opportunities in an environment of constrained resources. The data demonstrated that entrepreneurial leaders with accumulated social capital and habitus, who understand the dramaturgical context of an emergent technology field, can use forms of expert pragmatic knowledge to navigate the complexity in pursuit of a vision

Using Technology Enabled Qualitative Research to Develop Products for the Social Good, An Overview

This paper discusses the potential benefits of the convergence of three recent trends for the design of socially beneficial products and services: the increasing application of qualitative research techniques in a wide range of disciplines, the rapid mainstreaming of social media and mobile technologies, and the emergence of software as a service. Presented is a scenario facilitating the complex data collection, analysis, storage, and reporting required for the qualitative research recommended for the task of designing relevant solutions to address needs of the underserved. A pilot study is used as a basis for describing the infrastructure and services required to realize this scenario. Implications for innovation of enhanced forms of qualitative research are presented

Device Discovery in Frequency Hopping Wireless Ad Hoc Networks

This research develops a method for efficient discovery of wireless devices for a frequency hopping spread spectrum, synchronous, ad hoc network comprised of clustered sub-networks. The Bluetooth wireless protocol serves as the reference protocol. The development of a discovery, or outreach, method for scatternets requires the characterization of performance metrics of Bluetooth piconets, many of which are unavailable in literature. Precise analytical models characterizing the interference caused to Bluetooth network traffic by inquiring devices, the probability mass function of packet error rates between arbitrary pairs of Bluetooth networks, and Bluetooth discovery time distribution are developed. Based on the characterized performance metrics, three scatternet outreach methods are developed and compared. Outreach methods which actively inquire on a regular basis, as proposed in literature, are shown to produce lower goodput, have greater mean packet delay, require more power, and cause significant delays in discovery. By passively remaining available for outreach, each of these disadvantages is avoided

Estimating Transit Ridership Patterns through Automated Data Collection Technology: A Case Study in San Luis Obispo, California

Public transportation offers a crucial solution to the travel demand in light of national and global economic, energy, and environmental challenges. If implemented effectively, public transit offers an affordable, convenient, and sustainable transportation mode. Implementation of new technologies for information-harvesting may lead to more effective transit operations. This study examines the potential of automated data collection technologies to analyzing and understand the origin-destination flow patterns, which is essential for transit route planning and stop location placement. This thesis investigates the collection and analysis of data of passengers onboard San Luis Obispo Transit buses in February and March 2017 using Bluetooth (BT) and automatic passenger counter (APC) data. Five BlueMAC detectors were placed on SLO Transit buses to collect Bluetooth data. APC data was obtained from San Luis Obispo Transit. The datasets were used to establish a data processing method to exclude invalid detections, to identify and process origin and destination trips of passengers, and to make conclusions regarding passenger behavior. The filtering methods were applied to the Bluetooth data to extract counts of unique passenger information and to compare the filtered data to the ground-truth APC data. The datasets were also used to study the San Luis Obispo Downtown Farmer’s Market and its impact on transit ridership demand. The investigation revealed that after carefully employing the filters on BT data there were no consistent patterns in differences between unique passenger counts obtained from APC data and the BT data. As a result, one should be careful in employing BT data for transit OD estimation. Not every passenger enables Bluetooth or owns a Bluetooth device, so relying on the possession of Bluetooth-enabled devices may not lead to a random sample, resulting in misleading travel patterns. Based on the APC data, it was revealed that transit ridership is 40% higher during the days during which Higuera Street in Downtown San Luis Obispo is used for Farmer’s Market – a classic example of tactical urbanism. Increase in transit ridership is one of the aspects of tactical urbanism that may be further emphasized. With rapidly-evolving data collection technologies, transit data collection methods could expand beyond the traditional onboard survey. The lessons learned from this study could be expanded to provide a robust and detailed data source for transit operations and planning

Harnessing Technology: analysis of emerging trends affecting the use of technology in education (September 2008)

Research to support the delivery and development of Harnessing Technology: Next Generation Learning 2008–1

Internet de las cosas y la Salud centrada en el Hogar

Este artículo presenta una revisión del concepto de Internet de las Cosas y su aplicación en el área de la salud, centrándonos en las soluciones que existen actualmente para el manejo de la salud orientada al hogar. El internet de las cosas aplicado al campo de la salud, permitirá que muchas personas, independientemente de su clase social, utilicen los servicios que por medio de estas tecnologías se podrían ofrecer y que en muchos países ya se están empezando a implementar. Teniendo en cuenta que en las próximas décadas, el modelo de asistencia médica se transformará del presente hospital-céntrico que comúnmente conocemos a un modelo de salud totalmente centrado en el hogar, donde en el hogar se tendrá menor intensidad laboral y costo operacional. El servicio de salud en el hogar permite el aprovechamiento de la tecnología IoT, llamado muy a menudo como Salud IoT. Esto suena prometedor para la industria del sector salud y las TIC en general, porque permite personalizar el servicio sanitario, acelerando su evolución