Most of the signal processing that we will study in this course involves local operations on a signal, namely transforming the signal by applying linear combinations of values in the neighborhood of each sample point. You are familiar with such operations from Calculus, namely, taking derivatives and you are also familiar with this from optics namely blurring a signal. We will be looking at sampled signals only. Let's start with a few basic examples. Local difference Suppose we have a 1D image and we take the local difference of intensities, DI(x) = 1 2 (I(x + 1) − I(x − 1)) which give a discrete approximation to a partial derivative. (We compute this for each x in the image.) What is the effect of such a transformation? One key idea is that such a derivative would be useful for marking positions where the intensity changes. Such a change is called an edge. It is important to detect edges in images because they often mark locations at which object properties change. These can include changes in illumination along a surface due to a shadow boundary, or a material (pigment) change, or a change in depth as when one object ends and another begins. The computational problem of finding intensity edges in images is called edge detection. We could look for positions at which DI(x) has a large negative or positive value. Large positive values indicate an edge that goes from low to high intensity, and large negative values indicate an edge that goes from high to low intensity. Example Suppose the image consists of a single (slightly sloped) edge:

http://ieeexplore.ieee.org/iel5/5/31307/01456462.pdf

Linear systems

The Wireless sensor network play a vital role in collecting a Real – Time data, monitoring environmental conditions based on technology adoption. These sensor network is the combination of sensing, computation, and communication through a single tiny device. Here many tiny nodes assemble and configure themselves. It also controls actuators that extend control from cyberspace into the physical world. Here the sensor nodes communicate with the local peers rather than the high – power control tower or base station. Instead, of relying on a predeployed infrastructure, each individual sensor or actuator become part of the overall infrastructure. Here we have three hardware platforms that addresses the needs of wireless sensor netwoks. The operating system here uses an event based execution to support concurrency. The platform serves as a baseline and does not contain any hardware accelerators. . First platform serves as a baseline and it produces Operating system concepts for refining concurrency mechanisms. The second node validates the architectural designs and improve the communicational rates. The third node represents the full realization of the general architecture. Keywords— node, platform, concurrency.

A Wireless Sensor Network.

Advances in wireless communication are forging new possibilities for sensors. New sensors are equipping major systems around us with unparalleled intelligence as in the case of smart grids, smart homes, and driverless vehicles. Considering the current developments in the field of sensor networks, one feels that it has reached an interesting stage, where the role of the sensors becoming crucial in numerous applications. This all speaks volumes of the fact that sensors are going to be at the front and center of most of future technologies, needless to say the Internet of Things. Considering their vital role from futuristic perspective this survey reports variety of sensors along with their characteristics and applications, which impact human life and well-being. In addition, this survey considers recent prototypes, leading sensor manufacturers as well as major projects that have made use of sensors since the last decade. Moreover, significance of this effort is that integration possibilities of sensors with other networks and major technologies are discussed, while possible challenges and key benefits are highlighted. This research effort focuses the latest developments in the area of sensors and sensor networks as research gears up to meet the challenges of the emerging technologies and their applications particularly those that emphasize smart sensors.

Wireless Sensor’s Civil Applications, Prototypes, and Future Integration Possibilities: A Review

Internet of Things (IoT) represents a new paradigm in computing in which devices are connected to the internet and directly communicate with each other. Because these devices are generally thought to be wireless, small and cheap, in other words not very reliable, it is vital that we address the robustness problems in IoT.

Energy efficiency and robustness for IoT: Building a smart home security system

Automated systems have become deeply involved in our daily life these days. Every day new researches and solutions are introduced in the worldwide to utilize computer systems to satisfy human needs. In this project we propose a “Intelligent Home Security Monitoring System” (IHMS) using RSSI in Wireless Sensor Networks. This paper presents a system using Wireless sensor networks (WSNs) enabled smart home environments to create pervasive and ubiquitous applications, which give scalable services and context-aware to the end users. This system develops an application and reports its implementation on real WSN to provide remote home security. There is a plan to use variations in received signal strength indicator (RSSI) value to find intrusion activity at home. Architecture of an application has been presented consisting of Moteivs Tmote Sky motes and a base station. The application sends a piece of alarm as a short message (SMS) on cellular phone of the homeowner in case of any intrusion activity has been detected at home.

/pdf/intelligent-home-monitoring-using-rssi-in-wireless-sensor-4jw6ipap8r.pdf

Intelligent Home Monitoring Using RSSI in Wireless Sensor Networks

In this paper, a low-power consumption remote home security alarm system developed by applying WSN and GSM technology is presented. It can detect the theft, leaking of raw gas and fire, and send alarm message remotely. The hardware of this system includes the single chip C5081F310, wireless receiving and sending chip CC1100 as well as the SIMENS TC35 GSM module. The system software developed in C51 language has the ability of collecting, wireless receiving and sending data, and can send a piece of alarm short message to the user’s mobile phone when some dangerous condition has been detected.

/pdf/a-remote-home-security-system-based-on-wireless-sensor-vbr5vui6uy.pdf

A Remote Home Security System Based on Wireless Sensor Network and GSM Technology

An ETC system based on RFID technology uses radio wave to identify cars passing through the toll collection site and automatically debits toll rate from the car owner's pre-paid account. RFID technology and its application in highway ETC system is analyzed in this paper. SNMP is a kind of protocol that has been widely used in network management system for many years. Because of its easy use and strong expansibility, SNMP is suitable for network management of ETC system. After introducing the basic knowledge of SNMP, this paper studies how to use SNMP to manage the RFID readers and the toll collection workstations remotely.

Application of RFID and SNMP technology in highway electronic toll collection system

Deep subdomain generalisation network for health monitoring of high-speed train brake pads

Multi-agent deep reinforcement learning for task offloading in group distributed manufacturing systems

With the ever increasing complexity of cyber-physical system, the coupling and interconnection between distributed nodes lead to a complicated description in mathematics. For example, time delays cannot be ignored in the cyber-physical system modeling. And delay compensation often requires the delayed Multi-Input-Multi-Output (MIMO) system to be presented in state space model and all time delays to be combined to sole side of input or output. The aim of this paper is to model the MIMO system with multiple delays in state space form and simultaneously combine both input and output delays into output channel only. In this paper, following up with the modeling of Networked MIMO System, an observable state-space realization of delayed transfer function matrix is developed, including the case with repeated poles. Meanwhile, multiple time delays are combined and allocated to the output side only. Based on the observable state space model, an observer can be designed and contributed to the delay compensation. Derivation and simulation results prove that the resulting model of Networked Control System (NCS) through the proposed modeling method is equivalent with the original networked MIMO system with both input and output delays in terms of input-output relationship, and thus it can be used in the prospective observer-based delay.

Xiangyin Meng

Papers

A Remote Home Security System Based on Wireless Sensor Network and GSM Technology

Application of RFID and SNMP technology in highway electronic toll collection system

Deep subdomain generalisation network for health monitoring of high-speed train brake pads

Multi-agent deep reinforcement learning for task offloading in group distributed manufacturing systems

Observable State Space Realization of Networked MIMO System for a Novel Virtual Observer-Based Delay Compensation