John Sarik

Movers and shakers: kinetic energy harvesting for the internet of things

Numerous energy harvesting wireless devices that will serve as building blocks for the Internet of Things (IoT) are currently under development. However, there is still only limited understanding of the properties of various energy sources and their impact on energy harvesting adaptive algorithms. Hence, we focus on characterizing the kinetic (motion) energy that can be harvested by a wireless node with an IoT form factor and on developing energy allocation algorithms for such nodes. In this paper, we describe methods for estimating harvested energy from acceleration traces. To characterize the energy availability associated with specific human activities (e.g., relaxing, walking, cycling), we analyze a motion dataset with over 40 participants. Based on acceleration measurements that we collected for over 200 hours, we study energy generation processes associated with day-long human routines. We also briefly summarize our experiments with moving objects. We develop energy allocation algorithms that take into account practical IoT node design considerations, and evaluate the algorithms using the collected measurements. Our observations provide insights into the design of motion energy harvesters, IoT nodes, and energy harvesting adaptive algorithms.

Lab kits using the Arduino prototyping platform

We present a lab kit platform based on an Arduino microcontroller board and open hardware that enables students to use low-cost, course specific hardware to complete lab exercises at home. The platform is designed to be accessible to a wide range of students and easily adapted for other applications. Careful hardware selection allows existing laboratory exercises to be modified for use with the platform, and the platform enables new exercises that would not be possible in a traditional lab. We describe the adoption of these kits in a course designed for on-campus and remote students that teaches the science and technology of modern display systems. We find that the platform delivers a consistent, high quality laboratory experience for both on-campus and remote students.

Movers and Shakers: Kinetic Energy Harvesting for the Internet of Things

Numerous energy harvesting wireless devices that will serve as building blocks for the Internet of Things (IoT) are currently under development. However, there is still only limited understanding of the properties of various energy sources and their impact on energy harvesting adaptive algorithms. Hence, we focus on characterizing the kinetic (motion) energy that can be harvested by a wireless node with an IoT form factor and on developing energy allocation algorithms for such nodes. In this paper, we describe methods for estimating harvested energy from acceleration traces. To characterize the energy availability associated with specific human activities (e.g., relaxing, walking, cycling), we analyze a motion dataset with over 40 participants. Based on acceleration measurements that we collected for over 200 hours, we study energy generation processes associated with day-long human routines. We also briefly summarize our experiments with moving objects. We develop energy allocation algorithms that take into account practical IoT node design considerations, and evaluate the algorithms using the collected measurements. Our observations provide insights into the design of motion energy harvesters, IoT nodes, and energy harvesting adaptive algorithms.

Prototyping energy harvesting active networked tags (EnHANTs)

This paper focuses on a new type of wireless devices in the domain between RFIDs and sensor networks - Energy Harvesting Active Networked Tags (EnHANTs). Future EnHANTs will be small, flexible, and self-powered devices that can be attached to objects that are traditionally not networked (e.g., books, toys, clothing), thereby providing the infrastructure for novel tracking applications. We present the design considerations for the EnHANT prototypes, developed over the past 3 years. The prototypes harvest indoor light energy using custom organic solar cells, communicate and form multihop networks using ultralow-power Ultra-Wideband Impulse Radio (UWB-IR) transceivers, and adapt their communications and networking patterns to the energy harvesting and battery states. We also describe a small scale EnHANTs testbed that uniquely allows evaluating different algorithms with trace-based light energy inputs.

Energy-Harvesting Active Networked Tags (EnHANTs): Prototyping and Experimentation

This article focuses on a new type of wireless devices in the domain between RFIDs and sensor networks—Energy-Harvesting Active Networked Tags (EnHANTs). Future EnHANTs will be small, flexible, and self-powered devices that can be attached to objects that are traditionally not networked (e.g., books, furniture, toys, produce, and clothing). Therefore, they will provide the infrastructure for various tracking applications and can serve as one of the enablers for the Internet of Things. We present the design considerations for the EnHANT prototypes, developed over the past 4 years. The prototypes harvest indoor light energy using custom organic solar cells, communicate and form multihop networks using ultra-low-power Ultra-Wideband Impulse Radio (UWB-IR) transceivers, and dynamically adapt their communications and networking patterns to the energy harvesting and battery states. We describe a small-scale testbed that uniquely allows evaluating different algorithms with trace-based light energy inputs. Then, we experimentally evaluate the performance of different energy-harvesting adaptive policies with organic solar cells and UWB-IR transceivers. Finally, we discuss the lessons learned during the prototype and testbed design process.

Evaluating photovoltaic performance indoors

A new approach to evaluating photovoltaic performance under artificial illumination is demonstrated. Several photovoltaic technologies are characterized under a standardized set of conditions in which radiant intensity and spectral composition of a light source are systematically varied. The results underscore the importance of establishing clear standards for photovoltaic characterization in emerging fields like energy harvesting.

Demo: prototyping UWB-enabled enhants

Energy Harvesting Active Networked Tags (EnHANTs) are a new class of devices in the domain between RFIDs and sensor networks. EnHANTs will be small, flexible, and energetically self-reliant. Their development is enabled by advances in ultra-low-power ultra-wideband (UWB) communications and in organic semiconductor-based energy harvesting materials. In this demo, we present UWB-enabled EnHANT prototypes. Each prototype is based on a MICA2 mote integrated with a UWB Transceiver and an energy harvesting module (EHM) that allows demonstrating energy harvesting-adaptive communications. Additional information about EnHANTs is available at [2] and http://enhants.ee.columbia.edu.

A Laboratory-Based Course in Display Technology

A laboratory-based class in flat-panel display technology is presented. The course introduces fundamental concepts of display systems and reinforces these concepts through the fabrication of three display devices-an inorganic electroluminescent seven-segment display, a dot-matrix organic light-emitting diode (OLED) display, and a dot-matrix liquid crystal display (LCD). Instead of fabricating a device over multiple laboratory sessions, students fabricate a functional device in a single session. This approach to teaching fabrication provides students immediate results, can accommodate students with disparate backgrounds, and can be easily adapted and expanded. This paper discusses the laboratory design, its impact on student experiences, and possible improvements and extensions.

Demo: Organic solar cell-equipped energy harvesting active networked tag (EnHANT) prototypes

Energy Harvesting Active Networked Tags (EnHANTs) will be a new class of devices in the domain between RFIDs and sensor networks. Small, flexible, and energetically self-reliant, EnHANTs will be attached to objects that are traditionally not networked, such as books, furniture, toys, produce, and clothing. More information about the EnHANTs project is available at http://enhants.ee.columbia.edu. In this demo we present a small network of EnHANT prototypes. The current EnHANT prototypes are integrated with novel custom in-house-developed energy harvesting and communications hardware, namely organic solar cells and ultra-wide-band impulse radio (UWB-IR) transceivers. The demo showcases prototypes communicating using the novel UWB-IR transceivers and adapting their communications and networking parameters to the available environmental energy harvested by the organic solar cells.

Project-based learning within a large-scale interdisciplinary research effort

The modern computing landscape increasingly requires a range of skills to successfully integrate complex systems. Project-based learning is used to help students build professional skills. However, it is typically applied to small teams and small efforts. In this paper, we describe our experience in engaging a large number of students in research projects within a multi-year interdisciplinary research effort. The projects expose the students to various disciplines in Electrical Engineering (circuit design, wireless communications, hardware prototyping), Computer Science (embedded systems, algorithm design, networking) and Applied Physics (thin-film battery design, solar cell fabrication). While a student project is usually focused on one discipline area, it requires interaction with at least two other areas. Over 4 years, 115 semester-long projects have been completed. The students were a diverse group of high school, undergraduate, and M.S. Computer Science, Computer Engineering, and Electrical Engineering students. Some of the approaches we have taken to facilitate student learning are real-world system development constraints, regular cross-group meetings, and extensive involvement of Ph.D. students in student mentorship and knowledge transfer. To assess our approaches, we conducted a survey among the participating students. The results demonstrate the effectiveness of our methods. For example, 70% of the students surveyed indicated that working on their research project improved their ability to function on multidisciplinary teams more than coursework, internships, or any other activity.