Projects @ NESL


MetroInsight: Real-Time Interventions from Sensory Data Flows in Urban Spaces (Active)

The mission of the MetroInsight project is to build an end-to-end system for knowledge discovery using highly-dimensional sensor time-series and real-time data streams to support the metropolitan infrastructure through effective analytics, workforce development and policy support. Working with a strategically chosen set of city governments in the Southwest, utilities and companies, we have unique access to specialized metropolitan data providers and National initiatives that have not yet been accessible to pipelines such as those proposed here. The project aims to overcome the data deluge caused by noisy multimodal urban sensory data. It will pursue advances in models and methods to transform multimodal urban data to a lower dimensional population-level data suitable for dynamic processing, real-time monitoring and visualization. [ Details ]

BlueWater: Data Insights for Water Management (Active)

Our work has been around leveraging all (old and new) water quality data, putting it on cutting-edge middleware for holistic analysis regardless of their source, finding insights that people may use and validating them in live environment. [ Details ]

Energy and Water Sustainability

SpotLight: Personal Natural Resource Consumption Profiler (Active)

The impending energy and natural resource crisis forces us to research innovative ways of optimizing our resource consumption. Recent studies have shown that a better understanding of an individual’s energy consumption helps people to lower their energy footprint significantly. We propose SPOTLIGHT, a system that profiles an individual's natural resource consumption pattern in real time using wireless sensor network technology. [ Details ]

Smart and Sustainable Buildings: Sensing and Control for Improving Water and Energy use in Buildings (Active)

This is a collaborative project between University of California, Los Angeles and Indian Institute of Information Technology, New Delhi, India. Buildings are among the largest consumers of energy, both directly in the form of electricity, gas etc. as well as indirectly through consumption of water as part of the critical energy-water nexus that one must consider for true sustainability. The objective of this project is to develop the foundations of low-cost and easy-to-deploy sensing methods that provide observability into patterns and causes of energy and water consumption in a building, and run-time methods that use the sensory information for intelligent control of various buildings systems to minimize the direct and indirect energy use. The project team is collaborating with international academic and industrial collaborators who offer access to complementary experimental opportunities and unique opportunities to develop low-cost technologies that scale across different climatic and socioeconomic contexts. Key elements of the research include (i) Low-cost self-calibrating sensors that infer energy and water usage indirectly from side-band signals, (ii) Methods to reduce overall energy and water footprint by better management of building subsystems, by timely identification and repair of energy and water wasting physical degradations, and by providing information feedback and incentives to influence occupant behaviors, and (iii) Study of the impact of human, cultural and societal factors on privacy, safety, and user interaction mechanisms. The project has the potential of significant socioeconomic benefits by facilitating assessment of efficacy of conservation measures, targeting of incentives, auditing compliance with regulations, and facilities maintenance. The project also contributes to workforce development and training of students on energy challenges in a global socioeconomic context. This project is a part of NSF's US-India pervasive communications and computing collaboration (PC3) initiative. [ Details ]

HVACME: HVAC air velocity and condition sensor (Active)

HVAC(Heating, Ventilating and Air Conditioning) system is one of the biggest environment-maintaining systems inside a building, and also the most power consuming system [1]. It is crucial to control the usage of HVAC systems in order to reduce overall power consumption.

In this project, we design an airflow sensor node, which is capable to measure air velocity, temperature and humidity. The sensor node is able to log and transmit data via wireless link.

The airflow sensors proposed in this project will greatly help the control of HVAC systems, by

  • measuring the injection of heat through the HVAC system into a room,
  • detecting hot-spots in HVAC usage, providing guidance for building or rebuilding the system,
  • detecting abnormal usage of HVAC system.

In order to make the node suitable for existing HVAC systems deployment, we need to make the node as small as possible, and as lasting as possible, without loosing accuracy.

[1] U.S. Household Electricity Report, [ Details ]

EnergyMonitor: Design and Implementation of Monitoring and Actuation Platform for Energy Management in Office (Inactive)

Although the HVAC (Heating, Ventilation and Cooling) system dominate the total power consumption of modern buildings, the IT equipments from PCs to network and server equipment are becoming an increasing contributor to energy bills and carbon emissions. Recent study also shows that much of the energy consumption is due to the IT infrastructure. In a typical office where desktop computers make up a substantial component of working area, the energy savings would have been potentially remarkable if users could be made aware of energy using as well as wasting, and an effective strategy was employed to intelligently control these computers.

In this project, we propose a monitoring and actuation platform to address this issue. Our platform is essentially a system that incorporates several function modules including data sampling, data visualization, notification, analysis and control. The contribution of our platform can be divided into two aspects. One is that we organize meter/sensor data stream efficiently and present them in a way that clients can easily access them. The other is that we analyze the meter/sensor data and build an effective profile model for each user to predict the subjects activities, and further control subjects computer accordingly to reduce unnecessary energy waste. We demonstrate that our approach achieve a 12% energy savings on average. In addition, the rate of accuracy for prediction of occupant activities using our model reaches approximately 90%.

[ Details ]

Hardware Platforms

MBED Cradle: Simple Add-on Board for mbed (Active)

This device gives the mbed development board battery power and management, voltage regulation, and Ethernet and USB connectors. [ Details ]

Illumimote: Wide-dynamic-range, high-fidelity, multi-modal light sensor module (Inactive)

UCLA NESL & the UCLA Hypermedia Studio present the ‘Ping-Pong’ mote, a new light sensing module for the Mica mote platform. The Ping-pong mote achieves performance comparable to a commercial light intensity meter, while conforming to the size and energy constraints imposed by its application in wireless sensor networks. The Ping-pong mote was developed to replace the Mica sensor board (MTS310) whose slow response time and narrow dynamic range in light intensity capture is unsuitable to many applications, including media production. The Ping-pong mote features significantly improved SNR due to its adoption of high-end photo sensors, amplification and conversion circuits coupled with active noise suppression, application-tuned filter networks, and a noise-attentive manual layout. Unlike the MTS310, the Ping-pong mote can capture RGB color intensity (for color temperature calculation) and incident light angle (which discerns the angle of ray arrival from the strongest source). Our prototype demonstrated significantly faster response time (> 6x) and a much wider dynamic range (> 10x) in light intensity measurement as compared with the MTS310. The light-angle estimation results were well correlated with an average error of just 2.63°. Technical data, publications, and results coming soon. E-mail the project participants directly if you need immediate access. [ Details ]

Mobile Phone based Sensing

PICK: A Framework for Choosing Data Collectors in Participatory Sensing (Inactive)

In traditional sensor systems, one of the fundamental problems concerns the placement of sensors. The analogous problem in participatory sensing is choosing users to perform a particular data collection task. This talk will detail, PICK, a framework that is designed to help with this process. Specifically, the framework considers the capabilities in terms of sensors available by a particular user, the availability of the user to participate in terms of spatial and temporal contexts, the reputation of the user as a data collector, and the incentive cost associated with the user participating as elements involved in the process of choosing data collectors. [ Details ]



Privacy, Security, and Integrity

SensorSafe: A Privacy-aware Sensor Database System with Usable User Interface. (Active)

With the wide-spread use of mobile smartphones and body-worn sensors, continuous collection of sensor data about individuals becomes feasible, and many useful applications such as medical behavioral studies, personal health-care, and participatory sensing have emerged. Such applications have important privacy implications due to their nature of sharing personal sensor data. In addition, what is shared is not only the raw sensor data but also the information that can be inferred from the data, which raises more privacy concerns of users. This paper proposes SensorSafe, an architecture for managing such personal sensory information in a privacy-preserving way. Our architecture consists of multiple remote data stores and a broker so users can retain the ownership of their data and management of multiple users can be well supported. SensorSafe also provides a fine-grained access control mechanism by which users can define their own sharing rules based on various conditions including context and behavioral status. Users define their privacy preferences and review their data by using our web-based user interface. We discuss our implementation of the SensorSafe architecture and provide application examples to show how our system can support user privacy. Our performance evaluation results demonstrate that building applications using the SensorSafe architecture is feasible so user privacy can be better protected. [ Details ]

RFSN: Reputation-based Algorithms in Sensor Networks (Inactive)

Networks of wirelessly interconnected embedded sensors and actuators promise an unprecedented ability to observe and manipulate our physical world. Indeed, recent years have seen much research on understanding the fundamental properties of such networks, and on developing algorithms and hardware-software building blocks for cheap and energy-efficient implementation. However, as with almost every disruptive technology that has impacted human society, the benefits of Embedded Networked Sensing are accompanied by a significant risk factors and potential for abuse. If wireless sensor networks are really going to be the eyes and ears of our society, as envisioned by many, then one needs to answer the following question: How can a user trust the information provided by the sensor network?

Building sensor networks poses challenges of secure routing, node authentication, data integrity, data confidentiality and access control that are faced in conventional wireless and wired networks as well. In the realm of sensor networks these problems are even more challenging due to the resource constraint nature and the scale of these networks. Only recently, researchers have started developing customized cryptographic solutions for sensor networks. However, current security mechanisms for sensor networks focus on external attacks. They fail to protect against internal attacks where a subset of sensor nodes are compromised. Due to lack of physical security and tamper resistance, adversaries can recover the embedded cryptographic material from these nodes and subsequently pose as authorized nodes in the network. A wide variety of sensor network applications such as forest fire monitoring, anti terrorism, bio/chemical agent monitoring etc. falls into the broad class of sense-response applications, where the system objective is to collaboratively detect the events and report the event detection back to the base station. The detection of an event is followed by some physical response such as sending special personnel, vehicles etc. to the location of the event. Compromised nodes can inject false data about non-existent events and authenticate them correctly to the user using their keys (false positive attacks), or stall the reporting of real events (false negative attacks). Thus, there is a need for developing a secure event reporting protocol.

Cryptographic keys form the backbone of any security protocol; the scale and ad-hoc deployment of nodes coupled with the ability of adversaries to easily recover the cryptographic materials make it a challenging problem to solve. In general the efficacy of any key establishment strategy needs to be gauged on the basis of both security metrics such as resiliency against node capture, node replication, access control measures and also on the complexity aspect such as scalability, storage etc. Existing key establishment techniques rely on a deterministic or probabilistic pre-distribution of keys in the network, trading off its performance on one metric with the other. We believe that a more apt approach in the realm of sensor networks is to derive them deterministically at runtime based on a single master key and unique physical attributes of the nodes.

Although cryptography and authentication help, they alone are not sufficient for the unique characteristics and novel misbehaviors encountered in sensor networks. We believe that in general tools from different domains such as economics theory, statistics and data analysis will have to be combined with cryptography for the development of trustworthy sensor networks. Fundamental to this is the observation that sensor network applications are based on collective interaction between a large numbers of nodes, which do collaborative data gathering, collective data/information processing, and multi-hop data delivery. This decentralized in-network decision-making, which relies on the inherent trust among the sensor nodes, can be abused by internal adversaries to carry out security breaches while generating information. An adversary can potentially insert bogus data to mislead the whole network! Clearly, cryptographic mechanisms alone cannot be used to solve this problem as adversarial nodes can use valid cryptographic keys to authenticate bogus data. Besides malicious attacks, the two other system characteristics that hinder the development of high integrity sensor networks are system faults and sensing channel inconsistencies. Sensor nodes are currently made of cheap hardware components, highly vulnerable to system malfunctioning. Non-malicious behavior such as radios/sensors going bust can also result in the generation of bogus data, bringing equally detrimental effects to the functioning of the whole network. Another distinguishing trait of sensor networks is there strong coupling with the physical world. This gives rise to a unique opportunity for adversaries, whereby instead of abusing the network, they can insert bogus data into the network by abusing the physical world. The very nature of these attacks is completely outside the realm of cryptography. [ Details ]

Sensor Data Integrity: Data Integrity in Sensor Networks (Inactive)

THis project explores methods and technologies for detecting data integrity problems in embedded sensor networks due to factors such as sensor failures, biofouling, and malicious compromise. [ Details ]

Lighthouse: Lighthouse (Inactive)

Many sensor network systems expose general interfaces to system developers for dynamically creating and/or manipulating resources of various kinds. While these interfaces allow programmers to accomplish common system tasks simply and efficiently, they also admit the potential for programmers to mismanage resources, for example through leaked resources or improper resource sharing. These kinds of errors are particularly problematic for sensor networks, given the resource constraints and lack of memory protection on current sensor platforms.

Lighthouse is a static analysis technique that brings the safety of static resource management to systems that dynamically manage resources. Our analysis is based on the observation that sensor network applications often manipulate resources in a producer-consumer pattern. In this style, each resource has a unique owner component at any given point in time, who has both the sole capability to manipulate the resource and the responsibility to properly dispose of the resource or transfer ownership to another component. Our analysis enforces this ownership discipline on components at compile time.

Lighthouse Website [ Details ]

QoI: Quality of Information in Sensor Networks (Inactive)

The goal of this project is to develop formal and rigorous approaches to reason about, and to optimize under resource constraints, the quality and value of sensor-based information flows. In large-scale distributed sensing, data from diverse sensor sources flow through increasingly higher-level inferences in a layered information fusion architecture to yield timely, actionable, trusted, and relevant intelligence information for decision makers. How well a particular information flow at a given level of abstraction conveys the true state of the world is formalized as Quality of Information (QoI), and is affected by a multitude of factors, such as: the integrity of the sensor sources; the characteristics of the network services; the nature of sensor information processing; the transformations that occur when information flows cross organizational, human-machine, and cultural boundaries; and, in the case of coalition operations, the policies governing information dissemination across coalition boundaries. How effective the information flow is for a particular use is formalized as Value of Information (VoI), and is a function of the information flow content, its QoI, and the decision making process (human or automated) that uses the information. [ Details ]

Wireless Communications

SDR: Software Defined Radio Research (Active)

An effort at NESL to investigate the technologies and and advances in Software Defined Radio. [ Details ]

ARI: Angle-of-Arrival Assited Relative Interferometry (Active)

Employ unique and common frequencies to identify and localize objects in the environment. [ Details ]

MIMAC: A rate-adaptive mac protocol for mimo-based wireless networks (Inactive)

It is envisioned that the next generation high-throughput wireless LAN standard (IEEE 802.11n), which is currently under development, would use MIMO technology to achieve high data rates. An important design consideration is maintaining backward compatibility with the IEEE 802.11a/g standards. In this context, we present a rate-adaptive MAC protocol for wireless networks with MIMO links. We adopt a joint MAC and physical layer strategy for channel access, based on the instantaneous channel conditions at the receiver. Our contributions include a transmit antenna and data rate selection scheme based on the optimal tradeoff between spatial multiplexing and diversity. The goal is to maximize the achievable data rate, given a MIMO channel instance and a target bit error rate. We also provide a feedback mechanism for the transmitter to obtain the rate selection settings from the receiver. Moreover, we maintain compatibility with legacy 802.11a/g devices and our protocol supports communication between devices with different number of antennas. The overall contribution is a MIMO physical layer aware, rate adaptive MAC protocol, which is compatible with 802.11a/g and can also be readily integrated with the 802.11n proposals. [ Details ]

CHBC: Channels Characteristics for On-Body Mica2Dot Wireless Sensor Networks (Inactive)

Biomedical applications in Sensor Networks attract many researchers’ focus, especially in the real-time health status monitoring field. However, the inconvenience of interconnecting sensors through wires not only induces high maintenance cost also limits freedom of human action. By attaching various types of bio-sensors to wireless sensor nodes, the unnatural wire constraints have been removed. The sampled data are transmitted through wireless interface and the system can response in time according to the different vital signs. Unlike wire connections, wireless connections are unstable and vulnerable to environments. It is our goal to study how the wireless links quality affected by human body, we attached sensor nodes onto different parts of human body, and monitor the packets received rate to learn how channels behave. We expect these experiment results can be used to assist the reliable and efficient connections for related biomedical researches [ Details ]

Sensor and Actuator Networks

Prudent Sampling: Prudent Sampling for Cyber-Physical Systems (Active)

In Cyber-Physical Systems the physical world influences the state of the various computation, communication, and storage processes via the sensing interface at which measurements of physical world variables are acquired and digitized for subsequent use in application-specific detection, estimation, inference, and control processes. Although its role is fundamental to the Cyber and the Physical, this interface receives little attention in system level design analysis, optimization, and verification. Typically, the interface between the continuous and the discrete halves is abstracted and idealized.

The ability to abstract the physical-world sampling interface stems from the perfect reconstruction assured by Shannon Sampling and enables designers to separate its concerns from the rest of the system. But, this relies on several implicit assumptions: that the act of sampling the physical world is cheap relative to the rest of the system, that Nyquist sampling is the best one could do, and that the performance and correctness of the rest of the system is decoupled from how the sampling interface is designed. These assumptions are often not true in practice.

Profligacy in sampling leads to a variety of energy, processing, communications, and even security bottlenecks at the system level. Our research investigates the impact on these bottlenecks of mechanisms that optimize the sampling and processing using adaptation and context-awareness while exploiting recent theoretical and embedded platform technology advances. Our goal in studying this is two-fold. First, we seek to systematically and jointly optimize and manage the various phases of the entire physical-to-cyber information-acquisition-and-processing pipeline for specific application objectives and system resource constraints. Second, we seek to develop methods to predict and validate the performance, resource requirements, and correctness of systems that make use of sophisticated sampling strategies with optimized analog, computation, communication, and storage processes. [ Details ]

JellyFish: Underwater Biomimetic Robotic Sensing (Active)

In this MURI project we are working with a team of researchers from Virginia Tech, UT Dallas, and others to create underwater robotic sensing platforms that mimic jellyfish. Our work at UCLA is focused on underwater sensing and communication modalities for the artificial jellyfish, with a particular focus on electric field based sensing and communication. [ Details ]

N/A: Sensor localization (Active)

Automatically identifying the context of a sensor - where it is located, what is located nearby, how does the user use it? Location is most concrete [ Details ]

CAASE: Coupled Animal and Artificial Sensing for Sustainable Ecosystems (Active)

This is a collaborative project funded by King Abdullah University of Science and Technology under Sensor Initiative: CASSE project. The mission of the CASSE project is to design and build a new purpose-built sensors and integrate with artificial platforms for ocean observation. We aim to create a new form of energy-efficient tag and track animals' movement. We plan to deploy the sensor tags onto the marine animals at Red Sea, Saudi Arabia. The project will also pursue advances in localization. Optimizing the duty-cycle of power-hungry GPS and other sensors, we will try to overcome the usual limitation of size and operating time. [ Details ]

Network Storage: Network Persistent Storage for Sensor networks (Inactive)

A major problem with sensor nodes today is their insufficient memory size, storage capacity, and power consumption while operating. This project explores the current options available for storing data on the motes and proposes a way to increase the storage capacity by using the StarGate as a base station. [ Details ]

Data Mule: Mobility for enhanced performance in sensor networks (Inactive)

Sensor Networks are being deployed to sense the environment. The data sensed(collected) at the various nodes is relayed to a base station using the wireless multihop network formed by the sensor nodes. The nodes nearer to the base station, acting as relays, risk running out of battery earliest. Once they die, the network becomes disconnected. I am looking at using controlled mobility to gather data from the sensor nodes. If the delay in data can be tolerated, the mobile element can visit these nodes periodically and get their data, thus reducing the relaying and increasing the lifetime. Recent research has involved deciding how and where the mobile should go. [ Details ]

sQualnet: Scalable Simulation Framework for Sensor Networks (Inactive)

Sensor networks are in wide spread use and with deployements reaching larger numbers, the need for a scalable simulation framework is becoming apparent. sQualnet provides this simulation framework. sQualnet, a scalable, extensible sensor network simulation framework, is built on top of commerically available state-of-the-art network simulator, Qualnet. sQualnet introduces a sensor stack parallel to the networking stack and provides accurate simulation models for various layers in the sensor and networking stack. It also includes a detailed and accurate power model. The sQualnet framework allows for hybrid testbeds by combining simulated nodes with real nodes. [ Details ]

Ragobot: Real Action Gaming Robots (Inactive)

There has been a dramatic shift in sensor networks towards the study of motile and mobile systems. Consider the classic target application of such a network – monitoring. Whether it's a forest fire, a platoon of soldiers, or a cosmic phenomenon, the overriding approach involves cheap nodes deployed throughout the area of interest. However, static sensor nodes suffer from numerous drawbacks. The pragmatic issues of network deployment, coverage holes, and sub-optimal density lend great credence to the addition of mobility.

Implementing these modern sensor networks requires a different design philosophy from traditional robotics. By convention, this field emphasizes the capability of a single robot; in contrast, mobile sensor nets leverage teams of coordinated entities. Estrin, conclude that two key requirements emerge: "support for very large numbers of unattended autonomous nodes and adaptivity to environment and task dynamics." In designing mobile sensor network devices, we discover that the former is actually an implicit benefit while the latter imposes significant design challenges.

Ragobot is the latest mobile sensor node to meet these constraints. Ragobot is smaller than most fully-navigable robots. and is more heavily instrumented (video capture, audio capture, processing, and playback, IR collision avoidance, IR cliff detection, RFID read/write, inertial navigation, and more) and mechanically advanced (capable of 34.9 degree vertical climb) than its smaller counterparts.

[ Details ]

Coordinated Actuation: Coordinated Actuation for Sensing Uncertainty Reduction (Inactive)

Motion may be used in sensor networks to achieve a desirable network configurations for improving the sensing performance. Mobility itself may have a high resource overhead, hence we exploit a constrained form of mobility which has very low overheads but provides significant reconfiguration potential. The objective is to maximize spatial coverage and resolution while simultaneously minimizing sensing resources. The project focuses on distributed methods to control the motion of the sensor nodes in response to the environmental dynamics and sensing demands. [ Details ]

ADCS: Distributed Control over Ad-hoc Sensor Actuator Networks (Inactive)

The emergence of pervasive networking technologies such as ZigBee and other low power radios, have opened up opportunities to apply wireless communication to several new applications. Control systems, earlier limited to wired star or bus topologies, may now use ad hoc wireless topologies where it facilitates deployment and maintenance. In this research we focus on a class of systems where a control operation is exercised over a system comprising of spatially distributed sensors and actuators that communicate through a wireless ad-hoc network. Such systems are emerging everywhere. A smart workspace that changes the lighting by sensing the user actions; A smart building that continuously reduces structural vibrations due to external disturbances; An intelligent irrigation system that micro-controls the soil conditions for precision agriculture. These are a few examples of a growing class of control applications.

A challenging issue for control over ad-hoc networks is the latency between sensor inputs and actuator outputs. Latency concerns can be addressed by operating the system in a distributed manner. However, an additional challenge then is to ensure coherent operation throughout the system without explicit central coordination. We design distributed ad hoc network algorithms to address these challenges.

A barrier to enabling end-to-end control applications is the difficulty in writing complex distributed embedded software for these systems. We provide a middleware service and a set of reusable components that abstract the low level timing and coordination details and provide an easy programming model for developers to quicly deploy their control applications.

[ Details ]

GALORE: Globally Ad-hoc LOcally REgular Systems (Inactive)

One of the challenges facing the system design is scalability. Centralized approaches fail due to latency (particularly for control based applications) and energy (determines the lifetime of the system). This forces us into a space where processing is co-located with sensing and the individual nodes are resource constrained. Such systems would have low-latency and be able to adapt to the environment. In this scenario, the GALORE project seeks to explore the hybrid space combining engineered subsystems and ad hoc global system structure. (GALORE  Globally Ad-hoc LOcally REgular). The focus is on localized approaches that do not rely on global knowledge or co-ordination. The motivating application for such a system is the unsupervised detection of the events of interest. [ Details ]