Nina Peterson

Home automation and security for mobile devices

As mobile devices continue to grow in popularity and functionality, the demand for advanced ubiquitous mobile applications in our daily lives also increases. This paper deals with the design and implementation of HASec, a Home Automation and Security system for mobile devices, that leverages mobile technology to provide essential security to our homes and associated control operations. In particular, with the help of mobile devices, HASec operates and controls motion detectors and video cameras for remote sensing and surveillance, streams live video and records it for future playback, and finally manages operations on home appliances, such as turning ON/OFF a television or microwave or altering the intensity of lighting around the house. The proposed home security solution hinges on our novel integration of cameras and motion detectors into a mobile application. For instance, when motion is detected, the cameras automatically initiate recording and the iOS device alerts the homeowner of the possible intrusion. HASec has two main components interacting with each other: the iOS application that executes on the mobile device and server-side scripts that run in a cloud. Although HA-Sec is implemented for Apples iOS devices such as iPhone, iPod Touch, and iPad, it can be easily ported to other mobile platforms. Furthermore, our application is not only limited to smart-phones but also can be used by feature phones through their browsers.

Real-World Sensor Network for Long-Term Volcano Monitoring: Design and Findings

This paper presents the design, deployment, and evaluation of a real-world sensor network system in an active volcano - Mount St. Helens. In volcano monitoring, the maintenance is extremely hard and system robustness is one of the biggest concerns. However, most system research to date has focused more on performance improvement and less on system robustness. In our system design, to address this challenge, automatic fault detection and recovery mechanisms were designed to autonomously roll the system back to the initial state if exceptions occur. To enable remote management, we designed a configurable sensing and flexible remote command and control mechanism with the support of a reliable dissemination protocol. To maximize data quality, we designed event detection algorithms to identify volcanic events and prioritize the data, and then deliver higher priority data with higher delivery ratio with an adaptive data transmission protocol. Also, a light-weight adaptive linear predictive compression algorithm and localized TDMA MAC protocol were designed to improve network throughput. With these techniques and other improvements on intelligence and robustness based on a previous trial deployment, we air-dropped 13 stations into the crater and around the flanks of Mount St. Helens in July 2009. During the deployment, the nodes autonomously discovered each other even in-the-sky and formed a smart mesh network for data delivery immediately. We conducted rigorous system evaluations and discovered many interesting findings on data quality, radio connectivity, network performance, as well as the influence of environmental factors.

A Lightweight Sensor Network Management System Design

In this paper, we propose a lightweight and transparent management framework for TinyOS sensor networks, called L-SNMS, which minimizes the overhead of management functions, including memory usage overhead, network traffic overhead, and integration overhead. We accomplish this by making L-SNMS virtually transparent to other applications hence requiring minimal integration. The proposed L-SNMS framework has been successfully tested on various sensor node platforms, including TelosB, MICAz and IMote2.

Optimized Autonomous Space In-Situ Sensor Web for Volcano Monitoring

In response to NASAs announced requirement for Earth hazard monitoring sensor-web technology, a multidisciplinary team involving sensor-network experts (Washington State University), space scientists (JPL), and Earth scientists (USGS Cascade Volcano Observatory (CVO)), have developed a prototype of dynamic and scalable hazard monitoring sensor-web and applied it to volcano monitoring. The combined Optimized Autonomous Space - In-situ Sensor-web (OASIS) has two-way communication capability between ground and space assets, uses both space and ground data for optimal allocation of limited bandwidth resources on the ground, and uses smart management of competing demands for limited space assets. It also enables scalability and seamless infusion of future space and in-situ assets into the sensor-web. The space and in-situ control components of the system are integrated such that each element is capable of autonomously tasking the other. The ground in-situ was deployed into the craters and around the flanks of Mount St. Helens in July 2009, and linked to the command and control of the Earth Observing One (EO-1) satellite.

TinyOS-based Quality of Service Management in Wireless Sensor Networks *

1 Abstract Previously the cost and extremely limited capabilities of sensors prohibited Quality of Service (QoS) implementations in wireless sensor networks. With advances in technology, sensors are becoming significantly less expensive and the increases in computational and storage capabilities are opening the door for new, sophisticated algorithms to be implemented. Newer sensor network applications require higher data rates with more stringent priority requirements. We introduce a dynamic scheduling algorithm to improve bandwidth for high priority data in sensor networks, called Tiny-DWFQ. Our Tiny-Dynamic Weighted Fair Queuing scheduling algorithm allows for dynamic QoS for prioritized communications by continually adjusting the treatment of communication packages according to their priorities and the current level of network congestion. For performance evaluation, we tested Tiny-DWFQ, Tiny-WFQ (traditional WFQ algorithm implemented in TinyOS), and FIFO queues on an Imote2-based wireless sensor network and report their throughput and packet loss. Our results show that Tiny-DWFQ performs better in all test cases.

Management and security of remote sensor networks in hazardous environments using over the air programming

Wireless Sensor Networks (WSNs) face many challenges including reliability, flexibility and security. When WSNs deployed in remote locations need to be reprogrammed, environmental conditions often make it impossible to physically retrieve them. Over the Air Programming (OAP) plays an important role in achieving this task. Additionally remote management of the WSN is crucial as it allows the user to monitor the download process. Cybersecurity of the WSN helps to ensure that the communication is properly authenticated. Several platform dependent protocols have been developed for OAP including Deluge and MOAP. Due to the restrictions of these platform-dependent protocols, any modifications to the hardware require modifications to the underlying protocol. For example, using OAP for iMote2 sensors requires porting Deluge from an existing hardware. We present the many challenges that we faced in making OAP possible on an iMote2 sensor network platform, including changes and upgrades to: file system management, Java toolbase and GUI implementation, reboot mechanism, robustness and boot loader. The performance of our OAP on the iMote2 platform is evaluated using a real sensor network along the completion time, overhead, and robustness dimensions.

Over the Air Programming on Imote2-Based Sensor Networks

Some of the main challenges that Wireless Sensor Networks (WSNs) face are reliability, flexibility and security. When WSNs deployed in remote locations need to be reprogrammed, environmental conditions often make it impossible to physically retrieve them. Over the Air Programming (OAP) plays an important role in achieving this task. Several platform dependent protocols have been developed for OAP including Deluge [4] and MOAP [3]. Due to the restrictions of these platform-dependent protocols, any modification to the hardware requires modifications to the underlying protocol. For example, using OAP for Imote2 sensors requires porting Deluge from an existing hardware. This paper reports the many challenges we faced in making OAP possible on an Imote2 sensor network platform, including changes and upgrades to: file system management, java toolbase and GUI implementation, reboot mechanism, and bootloader. The performance of our OAP on the Imote2 platform is evaluated using a real sensor network.

Volcano Monitoring: A Case Study in Pervasive Computing

Recent advances in wireless sensor network technology have provided robust and reliable solutions for sophisticated pervasive computing applications such as inhospitable terrain environmental monitoring. We present a case study for developing a real-time pervasive computing system, called OASIS for optimized autonomous space in situ sensor-web, which combines ground assets (a sensor network) and space assets (NASA’s earth observing (EO-1) satellite) to monitor volcanic activities at Mount St. Helens. OASIS’s primary goals are: to integrate complementary space and in situ ground sensors into an interactive and autonomous sensorweb, to optimize power and communication resource management of the sensorweb and to provide mechanisms for seamless and scalable fusion of future space and in situ components. The OASIS in situ ground sensor network development addresses issues related to power management, bandwidth management, quality of service management, topology and routing management, and test-bed design. The space segment development consists of EO-1 architectural enhancements, feedback of EO-1 data into the in situ component, command and control integration, data ingestion and dissemination and field demonstrations.

Fast track article: Design of smart sensing components for volcano monitoring

In a volcano monitoring application, various geophysical and geochemical sensors generate continuous high-fidelity data, and there is a compelling need for real-time raw data for volcano eruption prediction research. It requires the network to support network synchronized sampling, online configurable sensing and situation awareness, which pose significant challenges on sensing component design. Ideally, the resource usages shall be driven by the environment and node situations, and the data quality is optimized under resource constraints. In this paper, we present our smart sensing component design, including hybrid time synchronization, configurable sensing, and situation awareness. Both design details and evaluation results are presented to show their efficiency. Although the presented design is for a volcano monitoring application, its design philosophy and framework can also apply to other similar applications and platforms.

Authoring Adaptive Digital Computational Thinking Lessons Using vTutor for Web-Based Learning

Teaching style and personalized content delivery may have a significant impact on learning. While personalization for learners takes center stage in many research efforts, the same is not so true for teaching. A critical step in teaching is designing effective and customizable lesson plans using best-practices. In this paper, we present a web-based lesson plan design tool, called vTutor, that is designed keeping personalization for teachers in mind. We present and discuss content authoring using vTutor for web-based computational thinking classes.