Yusuf Ozturk

An Intelligent Home Energy Management System to Improve Demand Response

Demand Response (DR) and Time-of-Use (TOU) pricing refer to programs which offer incentives to customers who curtail their energy use during times of peak demand. In this paper, we propose an integrated solution to predict and re-engineer the electricity demand (e.g., peak load reduction and shift) in a locality at a given day/time. The system presented in this paper expands DR to residential loads by dynamically scheduling and controlling appliances in each dwelling unit. A decision-support system is developed to forecast electricity demand in the home and enable the user to save energy by recommending optimal run time schedules for appliances, given user constraints and TOU pricing from the utility company. The schedule is communicated to the smart appliances over a self-organizing home energy network and executed by the appliance control interfaces developed in this study. A predictor is developed to predict, based on the users life style and other social/environmental factors, the potential schedules for appliance run times. An aggregator is used to accumulate predicted demand from residential customers.

mPHASiS: Mobile patient healthcare and sensor information system

Pervasive care and chronic disease management to reduce institutionalization is a priority for most western countries. The realization of next generation ubiquitous and pervasive healthcare systems will be a challenging task, as these systems are likely to involve a complex structure. Such systems will consist of various devices, ranging from resource-constrained sensors and actuators to complex multimedia devices, supporting time critical applications. This is further compounded by cultural and socio-economical factors that must be addressed for next generation healthcare systems to be widely diffused and used. In this study, the requirements for a vital sign monitoring solution space is derived and mPHASiS is developed based on these requirements. mPHASiS is an end to end solution not only providing sensor networking and vital sign monitoring but also closing the loop by signaling alert messages to the caregiver and allowing pervasive access to vital signs of a patient using smartphones over a heterogeneous network. A role based access control mechanism is developed to limit access to sensitive data. The end to end delay and delay variations for both vital sign data collection and pervasive access are analyzed. mPHASiS is developed as a complementary solution augmenting functionality of a hospital information system and can be loosely couple with the hospital information system using webservices.

Requirements and design spaces of mobile medical care

Pervasive care and chronic disease management to reduce institutionalization is a priority for most western countries. The realization of next generation ubiquitous and pervasive healthcare systems will be a challenging task, as these systems are likely to involve a complex structure. Such systems will consist of various devices, ranging from resource-constrained sensors and actuators to complex multimedia devices, supporting time critical applications. This is further compounded by cultural and socio-economical factors that must be addressed for next generation healthcare systems to be widely diffused and used. These factors have a direct impact on the system and security models and will require further understanding to encourage users to embrace and adopt the new technology. These models must capture not only the perceived value of the new technology and its ease of use, but most importantly the perceived risk of using this technology. This paper outlines the design space of pervasive health monitoring with body sensor networks and derives the requirements for connected pervasive medical care systems. Commercial and academic mobile medical sensor systems have been mapped to the requirements derived and a comparative analysis of state of the technology is given.

Optimal time-of-use pricing for residential load control

Demand response (DR) can be defined as change in electric usage by end-use customers from their normal consumption patterns in response to change in the price of electricity over time. Demand Response also refers to incentive payments designed to induce lower electricity use at times of high wholesale market prices. Time-of-use (TOU) power pricing has been shown to have a significant influence on ensuring a stable and optimal operation of a power system. This paper presents a novel algorithm for finding an optimum time-of-use electricity pricing in monopoly utility markets; definitions and the relations between supply and demand as well as different cost components are also presented. Further, the optimal pricing strategy is developed to maximize the benefit of society while implementing a demand response strategy. Finally, the effect of demand response in electricity prices is demonstrated using a simulated case study.

A scalable distributed dynamic address allocation protocol for ad-hoc networks

Dynamic address allocation is an essential part in effective configuration and maintenance of a mobile ad-hoc network (MANET). In this paper, we present a new distributed dynamic address allocation protocol minimizing address allocation latency and communication overhead. Through analytic evaluation and experimental measurements, we show that scalability and faster recovery from failures can be achieved by dynamic address allocation. The dynamic address assignment protocol presented here requires a low memory footprint while supporting unicast, broadcast and multicast communication. A performance analysis of the proposed address allocation protocol is given in terms of address allocation latency and communication overhead. Node and Network mobility is addressed from the point of dynamic address management. The dynamic address allocation protocol is implemented on a TinyOS platform over a cluster tree network.

Antenna diversity using single antenna in robot communication

This study proposes to exploit multipath signals by repositioning a robot relay node within a quarter to one wavelength from its current position to improve signal quality. By mobilizing the communication node we offer a complementary solution to antenna diversity in environments where antenna diversity cannot be employed. The signal strength characterization is performed over a small area to study the impact of relocation of the node by a quarter to one wavelength. A new conjugate gradient search algorithm for exploiting combined multipath fading is proposed to improve signal quality between a mobile station and a set of other stations - mobile or fixed.

DIChirp: direct injection bandwidth estimation

Ideally, network bandwidth estimation algorithms should be independent of the end system performance. If end system capabilities are involved, then the measurement will be of the system throughput and will not indicate a correct assessment of network bandwidth. Packet dispersion-based active bandwidth estimation schemes including Pathload, TOPP and pathChirp use delay correlation where the network-induced delay on packets transmitted at certain rates is translated into bandwidth estimation. Since packet dispersion-based active measurement schemes use delay correlation, bandwidth estimations are distorted by the host protocol stack-induced delay variations. Studies revealed that the host protocol stack-induced delay variations due to context switching are stovepiped in the network-induced delay variations and impact the measurement process. This study explores the delay variations introduced by the host protocol stack in packet dispersion-based techniques. The impact of host protocol delay variations and context switching on bandwidth estimation is analyzed and a new active bandwidth estimation tool minimizing the impact of context switching is proposed. Direct Injection Chirp (DIChirp) bypasses the TCP/IP protocol stack and directly interfaces with the network hardware. It uses the kernel for scheduling the outgoing packets, thus achieving more accurate estimation of bandwidth. Experiments revealed that the host protocol and context switching-induced delay variations can be as high as 800µs and could result in bandwidth estimation errors near 20%. Experiments also revealed that the DIChirp is superior to the pathChirp implementation in performance estimation since the datapath utilized by DIChirp is less prone to delay variations induced by context switching.

A Wireless 32-Channel Implantable Bidirectional Brain Machine Interface.

All neural information systems (NIS) rely on sensing neural activity to supply commands and control signals for computers, machines and a variety of prosthetic devices. Invasive systems achieve a high signal-to-noise ratio (SNR) by eliminating the volume conduction problems caused by tissue and bone. An implantable brain machine interface (BMI) using intracortical electrodes provides excellent detection of a broad range of frequency oscillatory activities through the placement of a sensor in direct contact with cortex. This paper introduces a compact-sized implantable wireless 32-channel bidirectional brain machine interface (BBMI) to be used with freely-moving primates. The system is designed to monitor brain sensorimotor rhythms and present current stimuli with a configurable duration, frequency and amplitude in real time to the brain based on the brain activity report. The battery is charged via a novel ultrasonic wireless power delivery module developed for efficient delivery of power into a deeply-implanted system. The system was successfully tested through bench tests and in vivo tests on a behaving primate to record the local field potential (LFP) oscillation and stimulate the target area at the same time.

Resonant ultrasonic wireless power transmission for bio-implants

In this paper, we present the ultrasonic wireless power transmission system as part of a brain-machine interface (BMI) system in development to supply the required electric power. Making a small-size implantable BMI, it is essential to design a low power unit with a rechargeable battery. The ultrasonic power transmission system has two piezoelectric transducers, facing each other between skin tissues converting electrical energy to mechanical vibrational energy or vice versa. Ultrasound is free from the electromagnetic coupling effect and medical frequency band limitations which making it a promising candidate for implantable purposes. In this paper, we present the design of piezoelectric composite transducer, the rectifier circuit, and rechargeable battery that all packaged in biocompatible titanium can. An initial prototype device was built for demonstration purpose. The early experimental results demonstrate the prototype device can reach 50% of energy transmission efficiency in a water medium at 20mm distance and 18% in animal skin tissue at 18mm distance, respectively.

A new collaborative active learning tool for signal processing education

This paper introduces a distributed object based collaboration system called Collaboard, which can be effectively used to conduct signal processing classes in an interactive fashion. Collaboard allows a group of users in a heterogeneous network environment to share multimedia objects, such as text, geometric entities, equations, images, audio/video objects, and OLE/sup TM/ objects. Collaboard supports multiple user groups and allows a user to actively participate in multiple learning groups. Matlab/sup TM/ has been integrated into this Collaboard as the computational workhorse. The Matlab programs or tasks initiated by any participant are replicated over the network to every participant. Our Collaboard architecture is a distributed object-based tool supporting object video and object audio. The current version of the system includes a RealAudio/sup TM/ server to support streaming audio capability. We believe that the comprehensive and user-friendly architecture of this Collaboard will be a very powerful working tool for DSP/communication systems classes in active learning environment.