Exploring the Limits of System Integration with Smart Dust



Similar documents
ISSCC 2004 / SESSION 17 / MEMS AND SENSORS / 17.4

Multipath fading in wireless sensor mote

能 量 採 集 技 術 簡 介 及 發 展 現 況

Radio sensor powered by a mini solar cell the EnOcean STM 110 now functions with even less light

Implementation of Short Reach (SR) and Very Short Reach (VSR) data links using POET DOES (Digital Opto- electronic Switch)

White Paper: Pervasive Power: Integrated Energy Storage for POL Delivery

Overview of Energy Harvesting Systems (for low-power electronics)

Wireless Security Camera

Energy Harvesting in Practical Applications. Roy Freeland President, Perpetuum Ltd

Sensor network infrastructure for intelligent building monitoring and management system

Micro Power Generators. Sung Park Kelvin Yuk ECS 203

AN588 ENERGY HARVESTING REFERENCE DESIGN USER S GUIDE. 1. Kit Contents. 2. Introduction. Figure 1. Energy Harvesting Sensor Node

Implementing Energy Harvesting in Embedded System Designs

Wireless Precision Temperature Sensor Powers Itself, Forms Own Network, Enabling Easy Deployment in Industrial Environments

Vibration Measurement of Wireless Sensor Nodes for Structural Health Monitoring

Computer Aided Design of Home Medical Alert System

Nanocomputer & Architecture

Intelligent Fleet Management System Using Active RFID

A Promising Energy Source for Portable MEMS Devices

ISSCC 2003 / SESSION 10 / HIGH SPEED BUILDING BLOCKS / PAPER 10.5

8 Gbps CMOS interface for parallel fiber-optic interconnects

The Energy Harvesting Tipping Point for Wireless Sensor Applications

Product Datasheet P MHz RF Powerharvester Receiver

Open Architecture Design for GPS Applications Yves Théroux, BAE Systems Canada

A Study of Low Cost Meteorological Monitoring System Based on Wireless Sensor Networks

NATIONAL SUN YAT-SEN UNIVERSITY

ISSCC 2003 / SESSION 4 / CLOCK RECOVERY AND BACKPLANE TRANSCEIVERS / PAPER 4.7

SOLAR ENERGY HARVESTING

Collaborating Objects Workshop. Bart Van Poucke IMEC

Online Communication of Critical Parameters in Powerplant Using ZIGBEE

Acoustic/Electronic stack design, interconnect, and assembly Techniques available and under development

CIRCUITS AND SYSTEMS- Assembly and Printed Circuit Board (PCB) Package Mohammad S. Sharawi ASSEMBLY AND PRINTED CIRCUIT BOARD (PCB) PACKAGE

Why silicon MEMS? Silicon is a strong material... Photolithography. Micromachining. Dicing and packaging

Tire pressure monitoring

Design of Remote data acquisition system based on Internet of Things

Data Management in Sensor Networks

Access Control Using Smartcard And Passcode

Sensors and actuators are ubiquitous. They are used

Wireless Sensor Networks

A New Programmable RF System for System-on-Chip Applications

ERÖFFNUNG DES INNOVATIONSZENTRUMS ADAPTSYS

Small Satellite Attitude Determination With RF Carrier Phase Measurement

Water Quality Monitoring System Using Zigbee Based Wireless Sensor Network

ENERGY HARVESTED ELECTRONIC SHELF LABEL

Application of Wireless Sensor Network and GSM Technology: A Remote Home Security System

NVM memory: A Critical Design Consideration for IoT Applications

Evolving Bar Codes. Y398 Internship. William Holmes

Energy Harvesting Powered Wireless Sensor Node and Asset Tracking Solutions in Random Vibration Environments

Miniaturizing Flexible Circuits for use in Medical Electronics. Nate Kreutter 3M

A Surveillance Robot with Climbing Capabilities for Home Security

The design and implementation of the environment monitoring system of smart home based on EnOcean technology

How to Improve Tablet PCs and Other Portable Devices with MEMS Timing Technology

Wireless Sensor Network: Challenges, Issues and Research

GP2Y0A02YK0F. Distance Measuring Sensor Unit Measuring distance: 20 to 150 cm Analog output type GP2Y0A02YK0F

State-of-Art (SoA) System-on-Chip (SoC) Design HPC SoC Workshop

DESIGN ISSUES AND CLASSIFICATION OF WSNS OPERATING SYSTEMS

Demystifying Wireless for Real-World Measurement Applications

Bus Data Acquisition and Remote Monitoring System Using Gsm & Can

FLYPORT Wi-Fi G

Micro-Power Systems for Ambient Intelligence

Software design for self-sustaining embedded systems

Case Study Competition Be an engineer of the future! Innovating cars using the latest instrumentation!

Micro-optical switches for future telecommunication payloads : achievements of the SAT 'N LIGHT Project

Micro-Power Generation

III. MEMS Projection Helvetica 20 Displays

2.45 GHz Power and Data Transmission for a Low-Power Autonomous Sensors Platform

Wireless Sensor Network Based Low Power Embedded System Design For Automated Irrigation System Using MSP430

Alessia Garofalo. Critical Infrastructure Protection Cyber Security for Wireless Sensor Networks. Fai della Paganella, 10-12/02/2014

PLICSMOBILE: Measurement data via the mobile network

CYBER PHYSICAL IIS

MXD7202G/H/M/N. Low Cost, Low Noise ±2 g Dual Axis Accelerometer with Digital Outputs

A Highly Efficient Power Management System for Charging Mobile Phones using RF Energy Harvesting

RFID BASED VEHICLE TRACKING SYSTEM

Monitoring of Intravenous Drip Rate

Automated Security System using ZigBee

Sensor Devices and Sensor Network Applications for the Smart Grid/Smart Cities. Dr. William Kao

Wi-Fi Backscatter: Battery-free Internet Connectivity to Empower the Internet of Things. Ubiquitous Computing Seminar FS2015 Bjarni Benediktsson

IEEE Projects in Embedded Sys VLSI DSP DIP Inst MATLAB Electrical Android

Volumes. Goal: Drive optical to high volumes and low costs

The Development of Space Solar Power System Technologies

Plc Based Monitoring and Controlling System Using Wi-Fi Device

Implementation of Wireless Gateway for Smart Home

RC2200DK Demonstration Kit User Manual

ELECTRICAL AND COMPUTER ENGINEERING By Joan Omoruyi, Engineering Librarian, Northeastern University

SCOOP: The Future of NDBC Real-Time Data Collection and Reporting

STUDENT PROFILES M.TECH IN RADIO FREQUENCY DESIGN AND TECHNOLOGY

Transcription:

Proceedings of IMECE 02 2002 ASME International Mechanical Engineering Congress & Exposition New Orleans, Louisiana, November 17-22, 2002 IMECE2002-34360 Exploring the Limits of System Integration with Smart Dust Brett A. Warneke, Kristofer S.J. Pister University of California, Berkeley Berkeley Sensor and Actuator Center 497 Cory Hall Berkeley, CA 94720-1774 {warneke,pister}@eecs.berkeley.edu ABSTRACT The Smart Dust project aims to explore the limits of system integration by packing an autonomous sensing, computing, and communication node into a cubic millimeter mote that will form the basis of massive distributed sensor networks, thus demonstrating that a complete system can be integrated into 1mm 3. Effectively exploring this space requires new approaches to design that emphasize energy and volume constraints over all others. To this end a 16 mm 3 autonomous solar-powered sensor node with bi-directional optical communication has been demonstrated, with smaller nodes forthcoming. System integration limits will shrink even further as carbon nanotube technology matures. INTRODUCTION In recent decades there have been dramatic reductions in the size of computational devices, sensors, and wireless communication. In addition, there has been an increasing amount of integration among these three areas and power supplies, creating systems with more functionality in smaller packages. Extrapolating these trends, we envision wireless sensor nodes becoming as small and as numerous as dust -- disappearing into the environment and dramatically changing the manner in which we interact with it. The Smart Dust project [1] was begun with the goal of investigating the limits of miniaturization and system integration by demonstrating that a useful and complex system can be built within a cubic millimeter. Specifically, the project is seeking to build an autonomous device that incorporates sensors, computation, wireless communication, and power source in a cubic millimeter mote that can be used in a distributed sensor network. Such devices would provide more information from more places in a less intrusive manner than ever before. Some example applications include defense networks that could be rapidly deployed by unmanned aerial vehicles (UAV), tracking the movements of birds, small animals, and even insects, fingertip accelerometer virtual keyboards, monitoring environmental conditions affecting crops and livestock, inventory control, and smart office spaces. The development of Smart Dust has required advances in miniaturization, integration, and energy management. This paper will discuss the philosophy of design that has been necessary to really explore this space, describe the mote architecture and components, show the current realizations of the system, then briefly discuss future limits. DESIGN PHILOSOPHY To really push the limits one must first eliminate any commitment to existing standards, protocols, packaging techniques, etc. that can add overhead and decrease efficiency. While these standards have their place and have played an important role in the success of certain technologies, they can prevent one from really approaching the limits and thus opening up new applications. For example, the IEEE 802.11b wireless network standard was designed for the high data rates needed by a computer network, but with some power consumption considerations since it was intended to be used in batterypowered devices such as laptop computers. Wireless sensor networks, on the other hand, have a substantially different usage model that includes much lower data rates and more spurious traffic that can lead to a dramatic reduction in the energy required to communicate a certain amount of information. 1 Copyright 2002 by ASME

Operation Digital inst. RX 1 bit TX 1 bit Sensor sample Sample, think, listen, talk Table 1: Energy Consumption and Battery Life Previous 200 Now <10 pj 12 pj 16 pj 31pJ 3 Ops/mm 3 battery >100 billion 83 billion 63 billion 32 billion 300 million Battery lifetime @ 100 ops/sec 32 years 26 years 20 years 10 years 9 years (1 set/sec) Ops/day*mm 2 indoor solar >100 million 83 million 63 million 32 million 300,000 (every 0.3 sec) Nevertheless, larger bridge nodes will exist to take advantage of network and data standards by interfacing with a wireless sensor network. A second design perspective that is critical when miniaturizing systems is that operations should be thought of in terms of energy. Because of the diminutive size of these devices and their wide dispersion, it will not be practical to change or recharge any batteries. Therefore, the energy stored in the battery limits the life of the mote and we can break down each operation into a particular energy cost to better guide our design decisions. Table 1 delineates this concept by showing the energy cost of various operations and how many operations a cubic millimeter of battery would yield. For example, an eight bit microprocessor instruction on a Smart Dust mote consumes less than 10pJ, so a 1J battery would only provide a little over 100 billion operations over its lifetime. Furthermore, one can translate component volumes into energy opportunity costs. With these figures, one can make trade-offs between computation, sensor sampling, communication, and volume. For instance, it may be advantageous to spend extra energy compressing data in order to save more energy during communication. One may also want to adjust the size of the transmitter and thus affect its energy efficiency as a trade-off with the size of the battery. THE SMART DUST ARCHITECTURE Figure 1 shows a conceptual diagram of a Smart Dust mote. As discussed above, the volume is expected to be dominated by the energy source, which will be an energy storage element such as a battery or capacitor, an energy harvester, or a combination thereof. A number of approaches to creating microbatteries are currently being pursued, including thick films, micromachined thin films [2], and micromachined cavities with an electrolyte [3]. From the system s perspective, a good microbattery would have the following features: 1. high energy density 2. large active volume to packaging volume ratio (i.e. a thin film on top of a 500µm silicon wafer would not be desirable) 3. small cell potential (0.5-1.0 V) so digital circuits can take advantage of the quadratic reduction in power consumption with supply voltage 4. efficiently configured into series batteries to provide a variety of cell potentials for the various components of the system without requiring the overhead of voltage converters 5. rechargeable in case the system has an energy harvester Microbattery technology is still heavily in the research phase, but current micromachined batteries can provide 5.6 J/mm 3 [2], which is competitive with large-scale batteries. Even though process compatibility with the other components of the system may seem desirable, it may actually not be important because of the possibility of stacking the components. Scavenging energy from the environment will allow the wireless sensor nodes to operate nearly indefinitely, without their battery dying. Solar radiation is the most abundant energy sourceandyieldsaround1mw/mm 2 (1 J/day/mm 2 )infull sunlight or 1 µw/mm 2 under bright indoor illumination. Solar cells have conversion efficiencies up to 30% and are a wellestablished technology, making them attractive for early use in sensor nodes. Vibration harvesting [4] is another potential energy source, scavenging energy from the vibrations of copy machines, ventilation systems, etc. More exotic energy sources include utilizing the excess heat from micro rocket engine combustion [5] and micro radioactive sources. Capacitors may be used in these systems to effectively lower the impedance of a battery or energy harvester to allow larger peak currents or to integrate charge from a energy harvester to compensate for lulls, such as nighttime for a solar cell. Current capacitors store up to 10 mj/mm 3. The next component of the Smart Dust mote is the sensor array. Micromachining has allowed researchers to shrink many types of sensors into small volumes while often maintaining similar, or even exceeding, performance levels of conventional transducers [6,7]. Monolithically integrating sensors together or Sensors Analog I/O, DSP, Control Figure 1. Mirrors Interrogating Laser Beam Passive Transmitter with Corner-Cube Retroreflector 1-2mm Laser Lens Mirror Active Transmitter with Beam Steering Power Capacitor Solar Cell Thick-Film Battery Photodetector and Receiver Smart Dust conceptual diagram. Incoming Laser Communication 2 Copyright 2002 by ASME

with other components such as the circuits can be advantageous because of the reduction in parasitics and area lost to pads, but placing them on disparate chips can be advantageous for stacking and packaging concerns of the micromachined structures. Free-space optical communication provides several advantages over RF communication for small, energyconstrained wireless nodes. First, optical radiators can be made more efficient as well as with much higher antenna gain (> 10 6 ) at the millimeter scale. Furthermore, optical transmitters are more power efficient at low power because of reduced overhead and since received power only drops as 1/d 2, compared with 1/ d 4 for RF transmissions subject to multi-path fading. Two compact approaches to free-space optical transmission include passive reflective systems and active-steered laser systems. The passive reflective system consists of three mutually orthogonal mirrors that form the corner of a cube (Fig. 1), hence the name corner cube retroreflector (CCR). Light entering the CCR bounces off each of the mirrors and is reflected back parallel to the incident beam. By electrostatically actuating the bottom mirror, the orthogonality can be broken, causing less light to return to the sender. The CCR can thus communicate with an interrogator by modulating the reflected light, with the only energy consumption being the charging of about 3pF in the actuator and a demonstrated range of 180m [8]. This technique consumes much less power than an approach that requires the generation of radiation, such as lasers or RF, but it does not facilitate peer-to-peer communication. Active-steered laser communication is currently under development. It would utilize an onboard light source, such as a VCSEL, a collimating lens, and MEMS beam-steering optics [9,10] to send a tightly collimated light beam toward an intended receiver, thus facilitating peer-to-peer communication. The final major aspect of the mote are the integrated circuits that tie all the pieces together. Analog signal conditioning circuitry and an analog to digital converter provide the interface to the sensors, while the receiver utilizes an integrated photodiode to sense optical transmission then decodes the data and timing information. Finally, a microcontroller orchestrates all of the functions of the mote, manages energy consumption, and stores data in an SRAM. All of these circuits are designed from the beginning to consume the minimum amount of energy to perform their given task. SYSTEM INTEGRATION At the top of the system stack is the software that controls the motes. TinyOS, an operating system developed for wireless sensor networks, is event-driven and supports efficient modularity and concurrency-intensive operation. The modularity is particularly important from a system integration perspective because the software modules in the operating system can be easily swapped for hardware components, and Figure 2. The Mica mote built from COTS components. It incorporates a coin cell battery, a radio transceiver, microcontroller, various sensors, and a module connector that allows a wide selection of expansion boards to be added. vice versa, allowing flexibility in the system components. This software is currently running on platforms such as is shown in Fig. 2, which is a cubic inch-scale mote built with commercial off-the-shelf components. TinyOS will eventually be ported to the cubic millimeter motes The current generation of Smart Dust mote (Fig. 3) is a 16mm 3 autonomous solar-powered sensor node with bidirectional optical communication. The device digitizes integrated sensor signals and transmits and receives data optically. The system consists of three die a 0.25µmCMOS ASIC, a trench-isolation SOI solar cell array, and a micromachined four-quadrant CCR. The dramatic size difference between the devices in Fig. 2 and Fig. 3 show the benefits of designing for low energy consumption and small size from the beginning. The next generation device will incorporate an ultra-low energy custom microcontroller and SRAM into the CMOS ASIC. Currently the mote is hand assembled, but microassembly techniques including microdomain pick and place and flip-chip bonding could be used to automate the process and even make the system more compact. Furthermore, process integration will combine the CCR, solar cell array, and accelerometer die into one in the next generation mote, shrinking it down to 6.6mm 3 and simplifying the assembly process. Packaging a cubic millimeter device obviously requires some innovative solutions. Some of the requirements are: 1. Protect the microstructures such as the CCR, accelerometer, and bond wires, while still allowing them to move. 2. Solar cells - clear packaging and possibly a lens 3. Receiver photodiode - optical filter 3 Copyright 2002 by ASME

even further. Of the four components necessary in a mote (sensing, computation, communication, and power), both sensing and computation have been demonstrated with carbon nanotubes [12,13]. Nanotubes and other nanotechnology devices may also play an important role in radio communication (as oscillators, filters, mixers, etc.), and power storage (hydrogen storage) [14] and generation (e.g. nano fuel cells). CONCLUSIONS Smart Dust has shown that system integration can be pushed down into the cubic millimeter-scale while maintaining a complex and useful system that incorporates computation, sensing, communication, and energy source. Further developments in microtechnology can reduce the size by perhaps a factor of ten, but nanotechnology should provide the next leap in the reduction of the limits. REFERENCES [1] B. Warneke, M. Last, B. Leibowitz, and K.S.J Pister, K.S.J., 2001, Smart Dust: Communicating with a CubicMillimeter Computer, Computer Magazine, Jan. 2001, pp. 4451. [2] W.C. West, et al., Fabrication and testing of all solid-state microscale lithium batteries for microspacecraft applications, J. Micromechanics and Microengineering, 12(2002), p. 58-62. Solar Cell Array CCR [3] K.B. Lee, L. Lin, Electrolyte Based On-Demand and Disposable Microbattery, MEMS 2002, Las Vegas, Nevada, 20-24 Jan. 2002, p.236-239. Receiver [4] S. Meninger, et al., Vibration-to-electric energy conversion, IEEE Trans. VLSI Systems, vol.9, (no.1), Feb. 2001, p.64-76. XL CMOS IC Photosensor [5] D. Teasdale, V. Milanovic, P. Chang, K.S.J. Pister, Microrockets for Smart Dust, Smart Materials and Structures, vol.10, (no.6), Dec. 2001, pp.1145-55. [6] Lj. Ristic [ed], Sensor Technology and Devices, Artech House, London, 1994. Figure 3. Mock-up of the 16mm3 autonomous solarpowered mote with bi-directional communications and sensing, composed of a 0.25µm CMOS ASIC, solar power array, accelerometer (not yet demonstrated in the system) and CCR, each on a separate die. 4. 5. [7] G.T.A. Kovacs, Micromachined Transduceers Sourcebook, WCB McGraw-Hill, San Francisco, 1998. [8] L. Zhou, K.S.J. Pister, J.M. Kahn, "Assembled Corner-cube Retroreflector Quadruplet", MEMS 2002, Las Vegas, Nevada, 20-24 Jan. 2002, p.556-559. CCR - anti-reflective (AR)-coated cover that allows illumination along its primary axis of [111]. [9] M. Last, et al., An 8 mm3 digitally steered laser beam transmitter, 2000 IEEE/LEOS Int l Conf. Optical MEMS, Kauai, HI, p. 69-70. Not add much extra volume The best proposed solution at this time incorporates potting the mote in an optical-quality polymer with some special molds. [10] V. Milanovic, M. Last, K.S.J. Pister, ``Torsional Micromirrors with Lateral Actuators,'' Trasducers'01 Eurosensors XV Conference, Muenchen, Germany, Jun. 2001. EXPLORING THE LIMITS IN THE FUTURE While Smart Dust is approaching a cubic millimeter mote with today s micro technology, future nanotechnology could conceivably push the limits of system integration size down [11] J. Hill, R. Szewczyk, A. Woo, S. Hollar, D. Culler, K. Pister, System architecture directions for networked sensors, 4 Copyright 2002 by ASME

ASPLOS-IX. Ninth International Conference on Architectural Support for Programming Languages and Operating Systems, Cambridge, MA, USA, 12-15 Nov. 2000, p.93-104. [12] M.S. Fuhrer, J. Nygard, L. Shih, M. Forero, Young-Gui Yoon, M.S.C. Mazzoni, Hyoung Joon Choi, Jisoon Ihm, S.G. Louie, A. Zettl, P.L. McEuen, Crossed nanotube junctions. Science, vol.288, (no.5465), 21 April 2000. p.494-7. [13] Jing Kong, N.R. Franklin, Chongwu Zhou M.G. Chapline, Shu Peng, Kyeongjae Cho, Hongjie Dai, Nanotube molecular wires as chemical sensors, Science, vol.287, (no.5453), 28 Jan. 2000. p.622-5. [14] Wang Qikun, Zhu Changchun, Liu Weihua, Wu Ting, Hydrogen storage by carbon nanotube and their films under ambient pressure, International Journal of Hydrogen Energy, vol.27, (no.5), May 2002. p.497-500. 5 Copyright 2002 by ASME