S. Muthulakshmi

Bio: S. Muthulakshmi is an academic researcher from VIT University. The author has contributed to research in topics: Computer science & Adder. The author has an hindex of 4, co-authored 8 publications receiving 53 citations.

IoT based water management

Abstract: Objectives: This project focuses on monitoring of use of water, consider, by one block of house in a flat system, where at the partition of pipeline from where the water gets diverted to various part of a block. Methods/Statistical analysis: Water places a vital role for living beings in their day to day lives. The earth's 71% is covered by water is a ubiquitous fact. Among which Oceans has approximately 96.50% and 3% is considered to be freshwater, again out of which only 0.08% is accessible direct to human use and rest is preserved in tundra regions and in different form on and in the earth surface which is very difficult to abstract for the human purposes. From this it states that only 0.08% is available as fresh water for human being to make use for drinking, domestic purposes, sanitation, manufacturing, leisure, agriculture etc which gets recharged by rain and snowfall 1. Findings: According to scientists and organizations as IPCC (Intergovernmental Panel on Climate Change), state has come, since a long time, where water management as such implies to maximizing use of water and minimizing the wastage of water and thus preventing the domino effect cycle arises as wastage of water. The sensors will sense the flow of water to each pipe which ultimately tells the usage of water at one block ideally. This water usage data would be sent to cloud using the IOT (Internet of things) space. This cloud data would be sent to the concern resident's person's mobile app (application) reporting the water used and alerting the user to limit the water use if it gets extended to the limit usage set by municipal government or corporation. If the limit gets extended the user have to pay accordingly. This will be real time operation. The objective of doing so is for limiting and minimizing the usage of water for an average of per person. And secondly, the cloud data will be used as statistic data for use of water at every seasons that is winter, summer and monsoon so that measuring steps for water management can be taken with the appropriate statistics, yielding an avenue for predictive measure. Improvements/Applications: To appraise the IOT based water management, it can be ramified as diligent, frugal for water management in a symbiotic parity way, which will constrict the water resource evenly according to the in situ factors.

Memristor augmented approximate adders and subtractors for image processing applications: An approach

Abstract: Approximate computing aims at reducing circuit complexity and delay, by allowing leverages in the output for a certain combination of inputs. The reduction in circuit complexity is achieved by minimizing the number of components in the circuit. This paper proposes a plausible approach towards approximate computing with memristors for designing memristor based approximate full adder and subtractor with logic minimization technique. The validation of our proposed approximate adder is verified by designing an 8-bit Ripple Carry Adder (RCA) to perform bitwise pixel addition of two gray scale images of the same size and compare the design with images obtained by exact addition method. Similarly, we have affirmed that the designed 8-bit Ripple Borrow Subtractor (RBS) is verified on foreground detection. Furthermore, to corroborate the above observation, performance metrics like Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Structural Content (SC), Mean Absolute Error (MAE), Average Distance (AD), Mean Average Distance (MAD) and Normalized Absolute Error (NAE) are deduced in MATLAB®. Owing to the logic minimization technique, for a certain combination of inputs, the MSE has been found to be predominant and its impact on PSNR is studied.

Global industrial process monitoring through IoT using Raspberry pi

Abstract: Objectives: With the fast increment in the quality of client of the internet over the previous decade has made the internet as a feature of the life and IoT is the most recent and developing innovation. Internet of Things (IoT) is developing systems of ordinary item from customer merchandise to mechanical machine that can share data and complete and while you are occupied with different exercises. This system is planned minimal effort and expandable permitting a variety of device to be monitored. In this project only sensors has been monitored for better result they has to be controlled wirelessly through IoT. Methods/Statistical analysis: All the sensors that are connected to the Atmega are sensing the values at different conditions and displaying the values in LCD as well as the values are stored in the cloud. Whenever there is a change in the measured parameter that changed values are being updated. This ensures the correctness of the system at every instant of time the values are automatically updated in the cloud. Findings: Global industrial process monitoring through IoT is a system that uses computer or mobile devices to monitor functions in industry. It is intended to spare electric force and human vitality. The sensors that can be checked are temperature, light intensity, water level, current and voltage. These sensors are associated with Atmega and interface with Raspberry pi and observed qualities are put away in cloud. The modern procedure monitoring system varied from other system by permitting the client to work the system from any place around the globe through internet association. The system will consequently change on the base of the sensors information. Application: Engineers and scientists around the world use embedded systems to prototype and diagnostics, monitoring, and control applications within a variety of demanding industry environments. Rugged and modular hardware provides the flexibility to meet your specific embedded system application needs today and in the future.

Raspberry Pi-Based Surveillance System with IoT

Abstract: Background: The proposed system describes a surveillance system developed using Raspberry Pi and a camera, which keeps monitoring a certain highly secured region continuously When the system recognizes a change in motion (human motion) compared to its previous frame, the system starts recording video and stores it primarily in its memory and also in the cloud (for the reason that even if the burglar tries to destroy the system his image/video will be saved in the cloud storage), and the user receives alert mail from the system stating “human motion detected” along with the captured image attached with the alert mail The system contains database of face patterns of local suspects which is compared with the face pattern of the person triggering the system, and image processing is done in real time to correctly identify the detected face; the system also keeps tracking the face throughout the region even if the person moves out of the frame by a camera mounted over a servo motor The system turns on a buzzer alarm when the burglar attempts to cause damage to the system The system allows the user to remotely access the camera to monitor live streaming video output and control the rotation of the camera Methods/Statistical analysis: In this project, different types of surveillance systems which already exist are analysed, and the methods of having a portable surveillance system were developed using Raspberry Pi Image processing methods for facial identification and face recognition is used Findings: A study based on various image processing techniques is done; it is found that Haar-cascade and linear binary pattern are the suitable algorithm for performing image processing in real time Application/Improvements: For better surveillance, face tracking in introduced, which can track the detected face throughout the region even if the person goes out of the camera frame, and remote accessing with control of the camera through IoT is introduced

IoT augmented health monitoring system

Abstract: Objectives: Post hospitalization care of a patient treated for critical illness, for instance cardiac arrest has been regarded as imperative. Nevertheless, it has become inevitable to skip follow-ups by the patients themselves. Method: This paper aims at designing a system which continuously monitors the health of the patient despite the patient being busy with his routine. An application is developed on android platform combined with Internet of Things (IoT) and sensor devices. Health of patient will be monitored by sensors and data from sensors will be sent to cloud which can be accessed anytime by the doctor and/or caretaker both in the cloud and application for necessary follow-ups in real time. Findings: In order to find the health of a patient more parameters are needed. But the main parameter for identifying the health of a patient are heart rate and temperatures. More parameters can be added to the system developed. Improvements/Applications: More sensors can be added to the system and the system has many application scenarios such as family health care.

Smart surveillance monitoring system using raspberry pi and pir sensor

Abstract: SMART SURVEILLANCE MONITORING SYSTEM USING RASPBERRY PI AND PIR SENSOR

Energy and area efficient imprecise compressors for approximate multiplication at nanoscale

Abstract: Approximate computing is a new paradigm for designing energy-efficient integrated circuits at the nanoscale. In this paper, we propose efficient imprecise 4:2 and 5:2 compressors by modifying the truth table of the exact compressors to achieve simpler logic functions with fewer output errors. The proposed approach leads to imprecise compressors with significantly fewer transistors and higher performance in comparison with their previous counterparts. Moreover, efficient approximate multipliers are designed based on the proposed imprecise compressors. The circuits are designed using FinFET as one of the leading industrial technologies and are simulated with HSPICE at 7 nm technology node. Furthermore, the approximate multipliers are used in the image processing applications, including image multiplication, sharpening and smoothing, and the peak signal to noise ratio (PSNR) and mean structure similarity index metric (MSSIM) as two important quality metrics are calculated using MATLAB. The results indicate significant improvements regarding performance, energy-efficiency, and the number of transistors compared to the other existing exact and approximate designs. The proposed 4:2 and 5:2 compressors improve the power delay product (PDP), on average by 59% and 68%, and area by 60% and 75%, respectively, in comparison with the previous designs. In addition, the proposed multipliers provide a significant compromise between hardware efficiency and accuracy for approximate computing. The proposed approximate multiplier using both imprecise 4:2 and 5:2 compressors improves the figure of merit, considering both image quality (based on PSNR and MSSIM) and energy efficiency, by 2.35 times as compared to its previous counterparts.

Design and analysis of multiplier using approximate 4-2 compressor

Abstract: Approximate computing has received significant attention as an attractive paradigm for error-tolerant applications to reduce the power consumption, delay and area with some trade-off in accuracy. This paper proposes the design of a novel approximate 4–2 compressor. A modified architecture of Dadda Multiplier is presented for the effective utilization of the proposed compressor and to reduce the error at the output. Through extensive experimental evaluation, the efficiency of the proposed compressor and multiplier are evaluated in a 45 nm standard CMOS technology and their parameters are compared with those of the state-of-the-art approximate multipliers. The results show that the proposed compressor accomplish a significant reduction in error rate compared to other approximate compressors available in the literature. In addition, the proposed multiplier shows 35%, 36% and 17% reduction in power consumption, delay and area respectively compared to those of exact multiplier. The effectiveness of multiplier is assessed by some of the image processing applications. On an average, the proposed multiplier processes images with 85% structural similarity compared to the exact output image.

BHMUS: Blockchain Based Secure Outdoor Health Monitoring Scheme Using UAV in Smart City

Abstract: Unmanned aerial vehicle (UAV) is an emerging technology that becomes popular not only in military operation but also in civil applications. Internet of things (IoT) is another popular technology which brings automation in our daily life. Like other areas, IoT also exposes its potential in healthcare. Using IoT sensors, it becomes easy to monitor the health of a user remotely. UAV consolidated with mobile edge computing (MEC) can provide real-time services in outdoor health monitoring. However, communication among them surrounds with cyber threats and data integrity issue. Blockchain is a data structure in which data are shared among peers. In this paper, a blockchain based secure outdoor health monitoring scheme using UAV is proposed for a smart city. In the proposed scheme, health data (HD) are accumulated from users wearable sensors and these HD are transmitted to the nearest MEC server via UAV. Prior to transmitting to MEC, HD experience encryption in order to provide protection against cyber threats. Moreover, after arriving at MEC, HD are diagnosed and if any abnormalities are found in the user’s health, MEC server notifies the user and the nearest hospitals. When the processing is completed, HD are stored in blockchain with the consent of validators. Finally, simulation results and experimental set up are discussed in order to manifest the feasibility of the proposed scheme.