Signal Processing for Wireless Sensor Networks Research Papers (original) (raw)

2024, IJIREEICE

A typical Wireless Sensor Networks is a multi-hop wireless network, is composed of large number of sensor devices. In case of routing protocols the wireless sensor network requirements are very specific, and it is the outcome of distributed nature and dynamic topology. There are many energy efficient algorithms which have been proposed in recent past. We may classify this algorithm on the basis of Reliable Routing, Network topology, Communication model and Network structure. We have analyzed and compared the performances of SEP and LEACH multiple routing protocols with our USEP on the basis of network lifetime and throughput.

2024, Scientific Reports

Today, wireless sensor networks (WSNs) are growing rapidly and provide a lot of comfort to human life. Due to the use of WSNs in various areas, like health care and battlefield, security is an important concern in the data transfer procedure to prevent data manipulation. Trust management is an affective scheme to solve these problems by building trust relationships between sensor nodes. In this paper, a cluster-based trusted routing technique using fire hawk optimizer called CTRF is presented to improve network security by considering the limited energy of nodes in WSNs. It includes a weighted trust mechanism (WTM) designed based on interactive behavior between sensor nodes. The main feature of this trust mechanism is to consider the exponential coefficients for the trust parameters, namely weighted reception rate, weighted redundancy rate, and energy state so that the trust level of sensor nodes is exponentially reduced or increased based on their hostile or friendly behaviors. Mor...

2024, International Journal of Computer Science and Information Technology

The efficiency of sensor networks strongly depends on the routing protocol used. In this paper, we analyze three different types of routing protocols: LEACH, PEGASIS, and VGA. Sensor networks are simulated using Sensoria simulator. Several simulations are conducted to analyze the performance of these protocols including the power consumption and overall network performance. The simulation results, using same limited sensing range value, show that PEGASIS outperforms all other protocols while LEACH has better performance than VGA. Furthermore, the paper investigates the power consumption for all protocols. On the average, VGA has the worst power consumption when the sensing range is limited, while VGA is the best when the sensing range is increased.

2023, Journal of information and communication convergence engineering

In this paper, we examine the problems of the low energy adaptive clustering hierarchy (LEACH) protocol and present ideas for improvement by selecting the cluster head node. The main problem with LEACH lies in the random selection of cluster heads. There exists a probability that the formed cluster heads are unbalanced and may remain in one part of the network, which makes some part of the network unreachable. In this paper, we present a new version of the LEACH protocol called the improved LEACH (ILEACH) protocol, which a cluster head is selected based on its ratio between the current energy level and an initial energy level, and multiplies by the root square of its number of neighbor nodes. The simulation results show that the proposed ILEACH increases the energy efficiency and network lifetime.

2023

Energy efficient clumping formation of nodes in Mobile Ad-Hoc Networks (MANETs) is very important as nodes in MANETs typically activate unattended with a limited power source. Energy efficient clumping formation in MANET is one of the major issue because energy of one node in clumping may affect all other nodes and also effect on the life time of the Clumping Head.In this paper, propose a newalgorithm technique - which is "Energy Efficient ClumpingBased Algorithm (EECBA)" on the bases of energy efficient routing and minimized the flooding strategies. It is emphasis that clumping maintenance and formation at low cost the resources used that aremobility and high battery power.This algorithmic technique reduce the routing overhead,increase the network life time. The Performance metrics are delay, Throughput. Thesimulation will be done using NS2 network Simulator.

2023, International Journal of Mobile Network Communications & Telematics

In this work, we propose a mechanism in which power consumption in a sensor network can be reduced greatly by taking into account the fairness factors and to increase the probability of nodes for successful packet transmission with lowest possible Signal to Noise Ratio (SNR) in a crowded environment. In other words we propose a high throughput and spectrally efficient network. The power consumption of the network reduces drastically when the clustered approach is adopted, which has been confirmed using the Friss transmission formula. Here, we have used analytical expressions from renewal reward theorem to deduce network throughput, probability of collisions and back-off periods upon collision in a random multiple access environment. Using those expressions we have made an analysis on network throughput, probability of collisions, bandwidth availability per node and estimation of back-off intervals upon collisions. The total number of nodes in the network is kept constant for observational purposes. The number of clusters has been varied to take observation of network throughput, probability of collisions, bandwidth availability per node and estimation of back-off intervals upon collisions. The analytical results obtained show that the power requirement of the network reduces drastically as the number of clusters increases.

2023, International journal of computer applications

A sensor network is nothing but the collection of number of wireless mobile nodes. Each node route the packet as well as forward the packet until the destination. Many routing protocol have been developed in mobile networks. Protocol selection is the main purpose of the wireless network and selected protocol must be best in all aspects of the mobile network. In this paper, simulation performance analysis is carried out on Adhoc On-demand Distance Vector (AODV), Destination Sequenced Distance Vector (DSDV) and Optimized Link State Routing (OLSR) protocol using NS3 simulator. The metrics used for performance evaluation are Throughput, Packet Delivery Ratio and Delay.

2023, Journal of emerging technologies and innovative research

The prominence of Wireless Sensor Networks have expanded hugely because of the huge capability of the sensor systems to associate the physical world with the virtual world. Since these gadgets depend on battery and might be put in hostile environment so replacing them becomes a tedious job. In this manner, improving the energy of these networks becomes significant. This paper provides methods for clustering and cluster head selection to WSN to improve energy efficiency. In this paper, we develop, analyze and compare Low-energy adaptive clustering hierarchy (LEACH), Stable Election Protocol (SEP) and ZonalStable Election Protocol (Z-SEP) to achieve good performance in terms of stability period, network lifetime and throughput.

2023, 2014 9th International Symposium on Communication Systems, Networks & Digital Sign (CSNDSP)

This paper considers energy efficiency of routing protocols in wireless sensor networks. Many routing protocols for sensor network have been proposed, some of them tried to cope with the ad-hoc nature while some others focus on improving the energy efficiency. We propose an Energy Harvesting Aware Ad hoc On-Demand Distance Vector Routing Protocol (AODV-EHA) that not only inherits the advantage of existing AODV on dealing with WSN's ad hoc nature, but also make use of the energy harvesting capability of the sensor nodes in the network, which is very meaningful to the data transmission in nominated environmental and military applications. Simulations results show the energy cost of data packet delivery along the route determined by proposed routing protocol has advantages over other existing competitors.

2023, Scientific Reports

In the fields of machine learning and artificial intelligence, recommendation systems (RS) or recommended engines are commonly used. In today’s world, recommendation systems based on user preferences assist consumers in making the best decisions without depleting their cognitive
resources. They can be applied to a variety of things, including search engines, travel, music, movies, literature, news, gadgets, and dining. A lot of people utilize RS on social media sites like Facebook, Twitter, and LinkedIn, and it has proven beneficial in corporate settings like those at Amazon, Netflix, Pandora, and Yahoo. There have been numerous proposals for recommender system variations.
However, certain techniques result in unfairly recommended things due to biased data because there are no established connections between the items and consumers. In order to solve the challenges mentioned above for new users, we propose in this work to employ Content‑based Filtering (CBF) and Collaborative Filtering (CF) with semantic relationships to capture the relationships as knowledge‑based book recommendations to readers in a digital library. When proposing things, patterns are more discriminative than single phrases. To capture the similarity of the books that the new user had retrieved, the patterns were grouped in a semantically equivalent manner using the Clustering method. The effectiveness of the suggested model is examined through a series of extensive tests employing Information Retrieval (IR) evaluation criteria. Recall Precision and F‑Measure, two of the three widely used performance measuring metrics, were employed. The findings demonstrate that the
suggested model performs noticeably better than cutting‑edge models.

2023, Building and Environment

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2023, 2012 Sixth International Conference on Next Generation Mobile Applications, Services and Technologies

We expect around 9 billions people on the Earth within 2050, 70% of them living in urban environments. By that time, we have to be ready to support a never seen request for ICT services in order to improve the efficiency of future Smart Cities, thus allowing a pacific coexistence among humans. In line with this premise, the present contribution proposes a novel service platform, based on the emerging content-centric networking paradigm. It can easily embrace all available, upcoming, and remote generation wireless techologies, while supporting, at the same time, ubiquitous and secure applications in many domains, such as: e-helthcare, intelligent transportation systems, entertainment, and many others. All details of the approach we propose, have been carefully described by means of pragmatical use-cases, thus making evident its effectivenes in future realistic urban environments.

2023, International Journal of Mobile Network Communications & Telematics

Wireless Sensor Network is a field of research which is viable in every application area like security services, patient care, traffic regulations, habitat monitoring and so on. The resource limitation of small sized tiny nodes has always been an issue in wireless sensor networks. Various techniques for improving network lifetime have been proposed in the past. Now the attention has been shifted towards heterogeneous networks rather than having homogeneous sensor nodes in a network. The concept of partial mobility has also been suggested for network longevity. In all the major proposals; clustering and data aggregation in heterogeneous networks has played an integral role. This paper contributes towards a new concept of clustering and data filtering in wireless sensor networks. In this paper we have compared voronoi based ant systems with standard LEACH-C algorithm and MTWSW with TWSW algorithm. Both the techniques have been applied in heterogeneous wireless sensor networks. This approach is applicable both for critical as well as for non-critical applications in wireless sensor networks. Both the approaches presented in this paper outperform LEACH-C and TWSW in terms of energy efficiency and shows promising results for future work.

2023, DIGITAL SMART ROOM

The concept of a digital smart room has emerged as a promising approach to enhance the functionality and connectivity within living spaces. A digital smart room integrates various smart devices, automation systems, and advanced technologies to create an intelligent and responsive environment. This abstract provides an overview of the key features and benefits of digital smart rooms. Digital smart rooms offer a seamless integration of Internet of Things (IoT) devices, allowing occupants to control and interact with their surroundings using voice commands or mobile applications. Lighting control systems enable the adjustment of light intensity, color, and timing, providing personalized lighting experiences. Similarly, climate control systems enhance comfort and energy efficiency by remotely managing temperature and ventilation settings. Entertainment systems within digital smart rooms provide occupants with the ability to stream music, movies, and TV shows from multiple sources, creating immersive audiovisual experiences. Integrated security and surveillance features, such as smart locks, motion sensors, and cameras, enhance the safety of the room, with remote monitoring and alerts in case of any suspicious activity. Automation plays a vital role in digital smart rooms, with automated window treatments optimizing natural light and privacy. Smart furniture with integrated technology further enhances convenience, with features like wireless charging capabilities and adjustable settings for personalized comfort. Energy management is a key aspect of digital smart rooms, as these systems monitor and optimize energy usage. By detecting room occupancy and adjusting settings accordingly, energy efficiency is maximized, contributing to sustainability and cost savings. The integration and control of all smart devices within the room are facilitated through centralized control hubs or mobile apps. This unified interface empowers occupants to customize settings, create automation routines, and monitor the status of devices, ensuring a personalized and user-friendly experience. In conclusion, digital smart rooms represent a significant advancement in home automation and connectivity. By leveraging IoT technologies, these rooms offer improved comfort, convenience, energy efficiency, and security. As research and development in this field continue to progress, the potential for digital smart rooms to revolutionize living spaces and enhance occupants' quality of life is vast.

2023, IEEE Access

To prolong the function of wireless sensor networks (WSNs), the lifetime of the system has to be increased. WSNs lifetime can be calculated by using a few generic parameters, such as the time until the death of the first node and other parameters according to the application. Literature indicates that choosing the most appropriate cluster head by clustering is one of the most successful ways to improve the lifespan of the WSN. The drawback of clustering protocols is based on the probabilistic model. Sometimes they select two cluster heads for two different clusters which are very close to each other and results in head situated at the edge of the cluster in some cases. This type of cluster head selection leads to a reduction in energy efficiency. Therefore, we have proposed the LEACH-Fuzzy Clustering (LEACH-FC) protocol and implemented a fuzzy logic-based cluster head selection and cluster formation to maximize the lifetime of the network. For selections of cluster head and formation of the cluster, we have used a centralized approach instead of distributed ones. We have also employed fuzzy logic in the selection of vice cluster head, which is also a centralized approach. The proposed algorithm has been found to be effective in balancing the energy load at each node thereby enhancing the reliability of WSN. It outperforms other proposed algorithms for improving network lifetime and energy consumption. INDEX TERMS Energy, fuzzy logic, centralized clustering, network lifetime.

2023, IEEE Sensors Journal

Providing automated granular control of lighting, along with user-driven control, results in an energy-efficient smart lighting system design while catering to personal occupant preferences. Two functional ingredients in such a system are: 1) sensing that provides granular information on occupant location and 2) a communication system to transmit control messages from a user. In this paper, we consider an ultrasonic circular array sensor that provides the dual functionality of granular occupant sensing and a communication receiver for user control transmissions. A ceiling-mounted sensor configuration with a colocated ultrasonic transmitter and array receiver is considered. To perform presence sensing, this transmitter sends periodic bursts of sinusoidal pulses that, upon reflection from the environment, are received at the array sensor. The echoes are processed to obtain estimates of range, azimuth, and elevation angles corresponding to possible occupant movements. A Kalman filter based on a near constant velocity model is used for target tracking. The resulting occupant location is used for energy-efficient lighting control. A user may in addition control lamps in its vicinity by sending messages at ultrasonic frequency, which are processed by the receiver array, and used to further adapt requested parameters of the lighting system. The proposed sensing and messaging solution is tested in an indoor office space with an eight-element receiver array sensor prototype.

2023, Buildings

Evaluating and optimising human comfort within the built environment is challenging due to the large number of physiological, psychological and environmental variables that affect occupant comfort preference. Human perception could be helpful to capture these disparate phenomena and interpreting their impact; the challenge is collecting spatially and temporally diverse subjective feedback in a scalable way. This paper presents a methodology to collect intensive longitudinal subjective feedback of comfort-based preference using micro ecological momentary assessments on a smartwatch platform. An experiment with 30 occupants over two weeks produced 4378 field-based surveys for thermal, noise, and acoustic preference. The occupants and the spaces in which they left feedback were then clustered according to these preference tendencies. These groups were used to create different feature sets with combinations of environmental and physiological variables, for use in a multi-class classific...

2023

Sensors, actuators, and controllers, which collectively serve as the backbone of cyberphysical systems for building energy management, are one of the core technical areas of investment for achieving the U.S. Department of Energy (DOE) Building Technologies Office's (BTO's) goals for energy affordability in the national building stock-both commercial and residential. In fact, an aggregated annual energy savings of 29% is estimated in the commercial sector alone through the implementation of efficiency measures using current state-of-the-art sensors and controls to retune buildings by optimizing programmable settings based on occupant schedules and comfort requirements, as well as detecting and diagnosing equipment operation and installation problems (Fernandez et al. 2017). Monitoring and control of building conditions and operations has advanced significantly, from the invention of the modern thermostat just before the start of the 20 th century to the midcentury incorporation of direct digital control into devices, the introduction of open protocols and network communications at the end of the century, and finally the invention of cloud-based computing and additional advancements that have enabled remote operation and a proliferation of connected and intelligent devices in building automation. Despite this potential, however, two main challenges hinder widespread adoption of sensors and controls in building operations that can ensure savings for high-efficiency components and equipment (e.g., heat pumps, windows, and lighting devices), as well as additional savings from more sophisticated control architectures and algorithms. First, centralized monitoring and control of operations through building automation systems (BAS) are prevalent in only 8% of floor space for small commercial buildings (<50,000 square feet) and 46% of floor space for large commercial buildings (>50,000 square feet) in the United States. This translates to 43% of the total floor space for the commercial building stock (U.S. Energy Information Administration [EIA] 2016). Similar to small commercial buildings, residential buildings typically do not have a centralized management system, although smart home assistants are beginning to take on this role. In the residential sector as of 2015, 41% of buildings had some type of programmable thermostat installed, but only 12% used the programmable functionality, and only 3% had a smart or learning thermostat that learns occupant behavior over time, eliminating the need for continual user activity (U.S. EIA 2017c). This number is steadily growing, with 40% of the 40 million thermostats sold in 2015 classified as smart (Parks Associates 2015). Second, most centralized systems currently installed exclusively manage heating, ventilating, and air conditioning (HVAC). These systems are typically separated from control of other building end uses such as common area lighting and plug loads. For example, home energy management systems usually consist of programmable thermostats for central and single-zone space conditioning, rather than more holistic management across multiple loads and appliances. Even modern systems incorporate a limited range of inputs and prescriptively map these inputs to control strategies to meet occupant needs and sometimes save energy. Much of installed equipment in buildings today is also not capable of digital communication and control. These conditions result in approaches that are customized in nature with new devices managing their own operation through built-in capabilities and intelligence. While efforts to embed intelligence in buildings that enable "smart" operations for energy management have proliferated in the past decade, they have generally lagged behind other sectors and applications (e.g., largescale industrial process plants, automotive, aerospace) due to several factors. These include utilization in less operationally critical applications (e.g., occupant comfort instead of safety and security); the fragmented nature of the buildings market (e.g., owner-owned and tenant-occupied); the customized nature of incorporating intelligence into building equipment rather than integrating into the design process; and the diversity of systems configurations and limited modeling and integration capabilities of stochastic variables (e.g., occupants, weather forecasts). As such, building controls are still predominately designed to meet short-term thermal and ventilation loads and are rule-based and reactive, rather than adaptive and autonomous, in nature. 2 Calculated based on EIA AEO 2017 data using Scout tool. 3 Cost premium based on 1-year payback period. 4 Full technical potential assuming no competition with measures from other technologies. 5 Based on all residential buildings; single/mobile homes use 0.0021 nodes/ft 2 floor and make up ~87% of all residential square footage (from residential EIA AEO 2017 microtables); multifamily homes use 0.0041 nodes/ft 2 floor and make up ~13% of all residential square footage (EIA AEO 2017 microtables). 6 Based on 0.002 nodes/ft 2 for large office commercial building. 7 Based on all commercial building types. INNOVATIONS IN SENSORS AND CONTROLS FOR BUILDING ENERGY MANAGEMENT: Research and Development Opportunities Report for Emerging Technologies xi INNOVATIONS IN SENSORS AND CONTROLS FOR BUILDING ENERGY MANAGEMENT: Research and Development Opportunities Report for Emerging Technologies xii 10 End uses labeled "other" include: for residential (small electric devices, heating elements, motors, swimming pool and hot tub heaters, outdoor grills, and any energy attributable to the residential buildings sector, but not directly to specific end uses) and for commercial (service station equipment, automated teller machines, telecommunications equipment, medical equipment, pumps, emergency electric generators, combined heat and power in commercial buildings, manufacturing performed in commercial buildings, and any energy attributable to the commercial buildings sector, but not directly to specific end uses).

2023, Signal & Image Processing : An International Journal

In this paper, blind image separation is performed, exploiting the property of sparseness to represent images. A new sparse representation called forward difference method is proposed. It is known that most of the independent component analysis (ICA) basis functions, extracted from images are sparse and gives unreliable sparseness measure. In the proposed method, the image mixture is first transformed to sparse images. These images are divided into blocks and for each block the sparseness measure 0 norm is applied. The block having the most sparseness is considered to determine the separation matrix. The efficiency of the proposed method is compared with other sparse representation functions.

2023, International Journal of Engineering & Technology

This paper highlights a number of recently published research studies during last five years in order to provide a summary related to latest trends of energy efficiency in the smart buildings technology. It reviews numerous technical methods applied to achieve a high level of Building Energy Efficiency (BEE). In this paper, methods applied to measure the BEE and to predict the energy-use have been considered and reviewed. Furthermore, some other methods discussed in articles which consider retrofitting of interior design of buildings have been taken. One of the most impacts that has been considered is the light control system because it directly affects the energy use. This paper has reviewed different types of techniques that save energy consumptions such as predictive techniques of energy use, Internet of Things (IoT) buildings, light control systems inside buildings, and Quick Response (QR) code based services used to notify occupants for energy-use. It has provided a simple comp...

2023, Proceedings of the 5th International Conference on Pervasive and Embedded Computing and Communication Systems

In this paper a new approach to complex comfort management is presented, aiming in automatic treatment of different comfort parameters by means of Internet-of-Things devices and multi-agent system. The paper presents a new model of e-comfort, based on common treatment of all the parameters as identified across the Maslow's hierarchy of needs. Next, a new architecture of e-comfort management is discussed, based on two layers: low-level layer of IoT devices, representing at-the-place possibilities of the system, and upper layer of software agents, formulating and negotiating the needs and expectations of human users.

2023, Energy and Buildings

Energy efficiency in buildings is a key issue in the current energy transition. In order to reduce building energy consumption, users' behaviour and the perception of indoor environmental comfort must be taken into account; these aspects are inextricably linked to energy demand, consumption and related costs. In this paper, we present the methodological framework, technological solutions and outcomes of the ComfortSense project. ComfortSense aimed at decoupling energy demand from indoor comfort. We focused on Heating, Ventilating and Air Conditioning (HVAC) systems in buildings, on users' behaviour and on comfort perception by treating buildings as socio-technical systems. Our approach-which was multidisciplinary and included the contribution of sociologists, physicists and computer scientists-was based on Internet of Things technologies, on a Living Lab design and testing process and on a Crowdsensing approach. Physical parameters (objective variables), such as temperature, CO 2 concentration and relative humidity, were measured by a Wireless Sensor Network and by wearable devices, while the users' perception of comfort (subjective variables) were recorded as real-time feedback through a Mobile App in three pilot buildings of the University of Turin, engaging about a thousand buildings' users (professors, researchers, students and employees). Objective and subjective variables were correlated through an ad-hoc Direct Virtual Sensor. Thanks to the Direct Virtual Sensor forecasting we demonstrated that, adopting an adaptive indoor comfort management, users' comfort can be remarkably improved while reducing the energy consumption of HVAC systems.

2023, Signal & Image Processing : An International Journal

2023, Procedia Computer Science

Commercial and residential buildings consume about 27% of total energy used in the US, out of which nearly half is consumed by commercial building sector and it expected to grow in the next 30-year period. Literature suggests that occupancy data may improve the energy consumption of the buildings, especially in HVAC operation. In the past few years studies came up with various frameworks based on existing infrastructure to estimate occupancy, out of which commodity WiFi gained popularity in detecting, estimating, and tracking occupants within buildings. However, there are concerns with those frameworks such as added infrastructure and computational efforts, upgrades to existing infrastructure, and privacy of occupants. This paper presents a simplistic framework based on commodity WiFi to estimate real time occupancy data without any added infrastructure or upgrades, while protecting the occupant privacy and can produce significant energy reduction in HVAC operation. The framework is tested on a large lecture hall in an institutional building that has multiple classes scheduled. The initial tests showed that the WiFi based occupancy had a 0.96 correlation with the established ground truth. Additionally, the WiFi based occupancy schedule resulted in at least 50% savings in HVAC energy consumption over static schedule.

2023, International Journal of Engineering and Technology

In this paper a novel Fuzzy based Stable Clustering Protocol (FSCP)for Heterogeneous Wireless Sensor Network (WSN)is proposed. The major focus of protocol is on network coverage and lifetime enhancement. It is observed that not only energy of sensor nodes but also the cluster headsdistancesaffect both network coverage and network lifetime. In this protocol, fuzzy logic with cluster head update rule is implemented to improve network coverage, throughput and network lifetime under multilevel heterogeneous network. For optimum number of cluster heads, probabilities of cluster heads are decided by fuzzy logic in which fuzzy logicselects CHs which have plenty of energy and satisfy distance criteria. Along this CH update rule also removes the unfavorable scenario of no CHs.These two factors, fuzzy logic and CH update rule better enhances the network performance when it is compared with LEACH, SEP, DEEC and EDCS protocol. Through simulation, it is justified that network coverage is improved by 17.50 % than EDCS protocol.

2023, International Journal of Advanced Smart Sensor Network Systems

In this research work, the egg laying radius of cuckoo search algorithm is used to create a cluster and then search for the optimum node based on multiobjective genetic algorithm with pareto ranking, so that the data can be forwarded to the sink.The primary focus is onthe two performance metrics parameters,one is the maximization of network lifetime and other is the minimization of delay. For maximizing the network lifetime parameter, the overlapped target sensing by many sensors is wastage of energy by two or more sensors, where the same task can be done by one sensor. To overcome this problem, the sequence set cover methodology is used.For minimization of delay parameter, the sleep-wake scheduling mechanism will be considered, but substantial delays are introduced as transmitting node needs to wait for its next-hop relay node to wake up. These delays can be taken care by developing any cast based packet forwarding schemes where individual node forwards a packet to the first neighboring node that wakes up among multiple candidate nodes. This any cast forwarding schemes minimizes the expected packet-delivery delays from the sensor nodes to the sink node. The introduced work will perform energy proficient routing with an objective to improve the network life, packet loss ratio and overall network throughput. The proposed algorithm was simulated in MATLAB and compared with LEACH algorithm. The results show that our proposed algorithm issuperiorfor prolonging the network lifetime, minimizing the packet loss and increasing the throughput.

2023, Sustainable Cities and Society

This paper deals with achieving both energy efficiency and comfortness in a particular room by controlling lighting and cooling appliances of a building by deploying modern sensors like Thermal sensors and Camera for accurate mapping of the environment parameters. The unique part of this paper is that a Sensor Fusion algorithm has been used in different segments of the room which combine the sensory output from the Thermal Sensor and Camera to ensure that the occupancy detection is done accurately with least amount of fluctuations without any delay. The two algorithms, namely, image processing algorithm and sensor signal processing runs in distributed computing environment in two different processors and the outputs of processing algorithms are received in the master controller through IoT cloud platform. The proposed image processing algorithm is effective in detecting both static and dynamic event changes using background subtraction and ROI based segregation models. The system develops the use of this sensor fusion algorithm to provide an intuitive control of the environment and improve the efficiency of the decision making process using National Instruments MyRIO 1800 and cRIO 9082 processors in LabVIEW platform which also reduces the chances or consequences of any fault occurring in the system.

2023

Smart city is a phenonmenon that integrates physical and social infrastructures with Information Technology to keep a city's cooperative intelligence under control. Smart cities primarily rely on Wireless Sensor Networks (WSN) to manage and maintain its service offerings. In literature, clustering and multihop routing techniques have been proposed, validated and implemented to reduce the consumption of energy in the network. With this motivation, the current study develops Adaptive Parallel Seeker Optimization-based Energy Aware Route Planning Technique (APSO-EARPT) for clustered WSN in smart cities. The presented APSO-EARPT technique concentrates on appropriate selection of Cluster Heads (CHs) and optimal routes in WSN. To accomplish this, APSO-EARPT model encompasses Weight-Based Clustering Scheme (WBCS) for effective selection of CHs. Then, routing process is performed with the help of APSO algorithm. The proposed APSO-EARPT technique computes a Fitness Function (FF) that comprises of three variables such as Residual Energy (RE), distance to Base Station (BS), and node degree. This fitness function helps in optimal selection of routes in WSN. In order to validate the supremacy of the proposed APSO-EARPT model in terms of network lifespan and energy efficiency, simulations were conducted and the results confirmed the excellent performance of the proposed model.

2023, Energy and Buildings

2023

The emergence of sensor networks as one of the dominant technology trends in the coming decades has posed numerous unique challenges to researchers. These networks are likely to be composed of hundreds, and potentially thousands of tiny sensor nodes, functioning autonomously, and in many cases, without access to renewable energy resources. Cost constraints and the need for ubiquitous, invisible deployments will result in small sized, resource-constrained sensor nodes. While the set of challenges in sensor networks are diverse, we focus on security of Wireless Sensor Network in this paper. We propose some of the security goal for Wireless Sensor Network. Further, security being vital to the acceptance and use of sensor networks for many applications; we have made an in depth threat analysis of Wireless Sensor Network. We also propose some countermeasures against these threats in Wireless Sensor Network.

2023

One of the key new features of connected lighting systems (CLS) is their ability to collect data from various types of integral sensors and share that data with other lighting or building systems. Occupancy and vacancy sensors have been widely adopted as an energy-saving strategy in buildings, yet published test methods for reproducibly characterizing their performance remain few and limited in their sophistication. As a result, it has been difficult to predict the performance of such sensors in a specific application, and in practice, they frequently do not meet energy-savings expectations. Occupants at times remove or otherwise bypass occupancy sensors that hinder their work or otherwise do not perform as expected, thereby compromising the sensors' potential to reduce energy consumption. Poor performance can result from multiple causes-ranging from fundamental limitations of the sensor technology, to misconfiguration, to poor placement in the room or space. Innovative occupancy sensors, some of them combining multiple sensing technologies (i.e., multimodal), have come on the market over the years, with claims of improved performance compared to their predecessors. However, in practice, their performance has neither differed enough from the performance of previous products to necessitate a test method that facilitated comparison between them, nor has it led to high deployment or high user satisfaction in human-occupied spaces with persistent presence. While the performance of both common and novel occupancy sensors has been the subject of many published research articles, the test methods that have been employed for them typically have been loosely described and have incorporated custom equipment or techniques that render them difficult to reproduce, or have been limited in their ability to fairly characterize devices that utilize varying sensor technology. The lack of a fully described, technology-agnostic test method that yields reproducible results across different implementations has been a barrier to the commercial success of new occupancy-sensor products, as users and specifiers who have been disappointed with previous products are often unwilling to take a chance with new ones. Motivated by a desire to fairly characterize new technologies that continue to enter the market and claim not only improved occupancy detection but, in some cases, additional capabilities (e.g., the ability to measure traffic or discern between different object types), this report presents the results of a literature review of recently published fully described test methods for characterizing occupancy-sensor performance, as well as research articles containing ad-hoc test methods. The review also identifies and consolidates test conditions for characterizing sensor performance in indoor spaces and identifies apparent test method gaps that need to be filled in order to evaluate emerging technologies and products. The identified test-method conditions are intended to enable the development of a future technology-agnostic test method that facilitates occupancy-sensor performance characterization more-accurately representing performance in buildings.

2022

There is an increasing interest in indoor occupation and guidance information for business and societal purposes. Scientific literature has paid attention to various ways of detecting occupation using different sensors as data source including various algorithms for estimating occupation rates from this data. Gaining meaningful insights from the data still faces challenges because the potential benefits are not well understood. This study presents a proof-of-concept of an indoor occupation information system, following the design science methodology. We review various types of sensor data that are typically available or easy-to-install in buildings such as offices, classrooms and meeting rooms. This study contributes to current research by incorporating business requirements taken from expert interviews and tackling one of the main barriers for business by designing an affordable system on a common existing infrastructure. We believe that occupation information systems call for further research, in particular also in the context of social distancing because of covid19.

2022, Proceedings of the 5th international conference on Future energy systems

Inferring human activity is of interest for various ubiquitous computing applications, particularly if it can be done using ambient information that can be collected non intrusively. In this paper, we explore human activity inference, in the context of energy consumption within a home, where we define an "activity" as the usage of an electrical appliance, its usage duration and its location. We also explore the dimension of identifying the occupant who performed the activity. Our goal is to answer questions such as "Who is watching TV in the Dining Room and during what times?". This information is particularly important for scenarios such as the apportionment of energy use to individuals in shared settings for better understanding of occupant's energy consumption behavioral patterns. Unfortunately, accurate activity inference in realistic settings is challenging, especially when considering ease of deployment. One of the key differences between our work and prior research in this space is that we seek to combine readily available sensor data (i.e. home level electricity meters and sensors on smartphones carried by the occupants) and metadata information (e.g. appliance power ratings and their location) for activity inference. Our proposed EnergyLens system intelligently fuses electricity meter data with sensors on commodity smartphones-the Wifi radio and the microphone-to infer, with high accuracy, which appliance is being used, when its being used, where its being used in the home, and who is using it. Ener-gyLens exploits easily available metadata to further improve the detection accuracy. Real world experiments show that EnergyLens significantly improves the inference of energy usage activities (average precision= 75.2%, average recall= 77.8%) as compared to traditional approaches that use the meter data only (average precision = 28.4%, average recall = 22.3%).

2022, 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)

In this paper, we propose a Space Inventory Management System (SIMS) framework that incorporates digital and analog data types to identify tangible space feature compositions as driving forces for user comfort and space choices. With a combination of real-time data from 3D stereo cameras and manually collected data points using a digitally advanced tool named ARCGIS PRO, the proposed framework get applied on a real case-An extension of a cafeteria area at the HL Lindner College of Business, USA. With the higher aim to synthesize different modern data streams and create a robust platform for extracting space features and their importance on behavioral outcomes, this article demonstrates the more significant opportunity of feeding human-centered information into the decision-making processes of future space designs.

2022, 2017 14th International Symposium on Pervasive Systems, Algorithms and Networks & 2017 11th International Conference on Frontier of Computer Science and Technology & 2017 Third International Symposium of Creative Computing (ISPAN-FCST-ISCC)

Humans are increasingly spending their time indoors. This, along with higher wealth levels and rise of internet of things, has provided designers and planners the opportunity to reimagine living spaces. Smart homes come in many different shapes, but to gain widespread acceptance they have to increase the utility of building occupants in some meaningful way. The most straightforward way of creating these smart homes is assumed to be through artificial intelligence. In this paper, we take a critical look at some algorithmic approaches that have been formulated to do so and the opportunities they will create in the short term. We also present some key challenges that must be overcome before these opportunities can be realized in practice.

2022, Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings

This is to certify that the thesis titled "WattShare: Detailed Energy Apportionment in Shared Living Spaces within Commercial Buildings" submitted by Shailja Thakur for the partial fulfillment of the requirements for the degree of Master of Technology in Computer Science & Engineering is a record of the bonafide work carried out by her / him under my / our guidance and supervision in the Mobile and Ubiquitous group at

2022, Proceedings of the 5th international conference on Future energy systems

2022, Mechanical Systems and Signal Processing

In sensed buildings, information related to occupant movement helps optimize important functionalities such as caregiving, energy management, and security enhancement. Typical sensing approaches for occupant tracking rely on mobile devices and cameras. These systems compromise the privacy of building occupants and may affect their behavior. Occupant detection and tracking using floor-vibration measurements that are induced by footsteps is a non-intrusive and inexpensive sensing method. Detecting the presence of occupants on a floor is challenging due to ambient noise that may mask footstep-induced floor vibrations. In addition, spurious events such as door closing and falling objects may produce vibrations that are similar to footstep impacts. These events have to be detected and disregarded. Tracking occupants is complicated due to uncertainties associated with walking styles, walking speed, shoe type, health, and mood. Also, spatial variation in structural behavior of floor slabs adds ambiguity to the task of occupant tracking, which cannot be addressed using data-driven strategies alone. In this paper, a framework for occupant detection and tracking is developed. Occupant detection is carried out based on signal information. This method outperforms existing threshold-based methods. Supportvector-machine classifiers, trained with time and frequency-domain features, successfully distinguish footsteps from spurious events and determine the number of occupants walking simultaneously. A model-based data-interpretation approach is used for occupant tracking. Structural-mechanics models are used to identify a population of possible occupant locations and trajectories. Up to two occupants can be tracked by accommodating systematic bias and uncertainties from sources such as modeling assumptions and variability in walking gaits. A hybrid framework for occupant detection and tracking that combines model-free approaches for occupancy detection with structural behavior models for tracking is developed and tested on two fullscale case studies. These studies successfully validate the utility of the framework for buildings having sparse sensor configurations that measure floor vibrations.

2022, International journal of Computer Networks & Communications

Wireless sensor networks (WSNs) are networks of sensor nodes that interact wirelessly to gather information about the surrounding environment. Nodes are often low-powered and dispersed in an ad hoc, decentralized manner. Although WSNs have gained in popularity, they still have several serious shortcomings, like limited battery life and bandwidth. In this paper, the cluster head (CH) selection, the Compressive Sensing (CS) theory, the Connection-based Decentralized Clustering (CDC), the relay node selection, and the Multi Objective Genetic Algorithm (MOGA)are all taken into account The initial stage provided a theoretical revision to the concepts of network construction, compressive sensing, and MOGA, which impacted the improvement of network lifetime. In the second stage developed a novel model such as Energy Aware Talented Clustering with Compressive Sensing (TCCS) for the sensor network. This approach considers increasing longevity but also raises the network's overall quality...

2022, International journal of Computer Networks & Communications

2022, International Journal of Engineering and Technology

2022, International journal of Computer Networks & Communications

2022, Sustainable Cities and Society

2022

The future developments of the wireless sensor networks and its applications demands for the efficient and secure communication. For the solution of efficient and reliable security needs cryptography algorithms provides good solutions. For providing reliable security schemes mainly data confidentiality now-a-days key management is used. This paper provides a review over cryptography schemes being used to deal with security issues of wireless sensor networks. ARTICLE HISTORY

2022, Energy and Buildings

2022, International Journal of Advanced Smart Sensor Network Systems

Wireless sensor networks (WSN) consist of many nodes that are usually created to identify environmental incidents. Each of these nodes includes sensor, processor, communication components (antenna), small memory, and a source of energy. In wireless sensor networks' applications, faulty nodes always cause crucial problems and error in the network. For example, failure of some nodes may pull some parts of network into isolation, or in a worse case, the entire network may stop working, or decision about the occurrence of events may be corrupted. This paper proposes a new method to detect faulty nodes in the WSN using fuzzy logic and majority voting technique. By using the attributes of the fuzzy logic like interpretation, etc. in corporate majority voting technique can overcome the problem of faulty nodes, efficiently. In the proposed method, the fuzzy logic uses to identify the ratio of the faulty nodes in the network and in each sub-network. Using the calculated ratio and an effective decision making system such as majority voting is used to detect the faulty node in WSN. Using this effective method increases the percentage of detecting faulty nodes, which resulted in decreasing computational complexity, end to end delay and energy consumption in WSN.

2022, Buildings

2022, International Journal of Communication Networks and Distributed Systems

Buildings are a major consumer of energy. We believe that energy can be saved with the notion of implicit occupancy sensing where existing IT infrastructure can be used to replace and/or supplement explicit dedicated sensors to determine building occupancy and drive building operation. Implicit sensing has the promise to be both lower in cost than explicit sensing based on PIR and ultrasound sensors and to offer additional useful data about the occupants of a building. Our implicit sensing methods are largely based on monitoring IP and MAC addresses in Wi-Fi access points and in routers, and then correlating these addresses to the occupancy of a floor, area, or room of a building. We experimentally evaluate the feasibility of this dual-use of IT infrastructure. We demonstrate an application of implicit sensing to sense the pending occupancy of a user workspace and automatically control the plugged-in devices in the workspace.