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 . 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
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. U.S. Household Electricity Report, http://www.eia.doe.gov/emeu/reps/enduse/er01_us.html [ Details ]
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 ]
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 ]
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 ]
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, et.al. 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 ]
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.
Sensor networks differ from traditional wireless networks in several respects. Unlike handheld wireless devices which can be recharged at reasonable frequent intervals, sensor nodes must operate autonomously for much longer durations. Energy supply thus remains an open challenge in sensor networks because unfettered deployment rules out traditional wall socket supplies and batteries with acceptable form factor and cost constraints do not yield the lifetimes desired by most applications.
One method to improve the battery lifetime of such systems is to supplement the battery supply with environmental energy. Several technologies exist to extract energy from the environment such as solar, thermal, kinetic energy, and vibration energy. However, we lack system level methods to efficiently exploit these resources for optimal performance. Sensor networks are expected to be deployed for several mission critical tasks and operate unattended for extended durations. The autonomous nature of operation makes it imperative that the system learn its own energy environment and adapt its power consumption accordingly. In distributed systems, not only does the energy source vary in time, but also the energy available at different locations, and thus at different nodes of the sensor network differs. In this situation, the performance can be improved by scheduling tasks according to the spatio-temporal characteristics of energy availability. The problem then, is to find scheduling mechanisms that can adapt the performance to the available energy profile.[ Details ]
The Power Aware Sensing Tracking and Analysis (PASTA) project is a DARPA-funded project that is investigating power-efficient systems for unattended ground sensor (UGS) applications. One of the applications that the project studies the tracking of moving vehicles using acoustic sensors. The NESL lab is involved in studying the effect of hierachical networks on the tracking cost and performance. The low tier of the hierarhical network comprises of small resource-contrained nodes (tripwires) such as the Berkeley motes as tripwire nodes. Higher tier nodes (trackers) perform sophisticated signal processing such as beamforming in order to estiamate the location of a moving vehicle using acoustic sensors.
Tripwire nodes consume low power and operate continuously to detect interesting events such as vehicles entering the field of interest. Upon detection tripwires wake up the more capable tracker nodes that perform the actual tracking of the intersting event. For more information about the project please visit the official project web page at USC/ISI East.[ Details ]
This web site contains information about the project "Design and Run-time Techniques for Physically Coupled Software" funded by the NSF Software for Real-world Systems program. This is a collaboration of NESL with research groups of Ramesh Govindan at USC, Rajesh Gupta at UCSD, and Paulo Tabuada at UCLA.
The research in this project seeks to establish the scientific principles governing software for real-world systems that are deeply embedded in the physical world, and whose operational behavior is determined in large part by a tight coupling between the system components and the physical environment. This objective is being accomplished by focusing on four challenges in the context of distributed sensing and control applications: 1) Support for physical context in the form of programming structures that enable application software to explicitly capture the state of the physical world as an observable in an embedded computation; 2) Formal methods for composing software modules that indirectly interact with each other through the physical world, and a run-time safety supervisor that provably enforces correctness of composition; 3) Programming structures to enable design and verification of applications with resource provisioning that is driven by and adapts to physical-world dynamics; 4) System software support for sharing physically-coupled sensor and actuator resources in distributed settings.
This material is based upon work supported by the NSF under awards # CCF-0820061, CCF-0820034, and CCF-0820230. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF. [ Details ]
The log instrumentation specification (LIS) language and runtime provides an extremely low overhead, portable, and easy to use framework for gathering runtime logs. The system is designed for application in wireless sensor networks where resource constraints stymie other attempts to expose runtime state.
The current implementation of LIS includes an instrumentation engine to instrument C code, full integration into the TinyOS build system, and plug-in analysis to perform common tasks built using LIS as an intermediary language.
For more information or for installation instructions go to the LIS website at:LIS Website [ Details ]