Detection and avoidance of water loss through municipality taps in India by using smart taps and ICT

Mohapatra, Hitesh; Rath, Amiya Kumar

doi:10.1049/iet-wss.2019.0081

Cited by 35 publications

(20 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Such hostile and harsh environment seriously needs such protocol where the sensors can sustain for a long period of time. Though the real-time demonstration is out of scope of this work but here we are providing few lists of refereed articles where such clustering algorithms will be fruitful [24][25][26][27][28][29].…”

Section: Results Discussionmentioning

confidence: 99%

Fault‐tolerant mechanism for wireless sensor network

Mohapatra

Rath

2020

IET wirel. sens. syst.

Self Cite

View full text Add to dashboard Cite

The study aims to understand the various types of faults occur in a wireless sensor network (WSN). The primary objective of the fault-tolerant technique is to enhance the robustness and self-healing capacity of sensor network. The resource constraint environment, remote deployment and harsh monitoring conditions frequently invite different types of faults in WSN. The fault can be handled in two ways such as fault tolerance and fault prevention method. The novelty of this state-of-art is, the authors propose two new algorithms named Uniform Energy Clustering for fault tolerance and Population-Based Clustering for fault prevention. The result of the simulation is satisfactory in comparison to existing algorithms such as Low Energy Adaptive Clustering Hierarchy, Stable Election Protocol, Virtual Area Partition-Energy and Energy-Aware Multi-Hop Multi-Path Hierarchical protocols. In addition to these new algorithms, they also propose a unique taxonomy on fault which is based on sensitivity issues of specific applications. PBC (Population-Based Clustering), which is a fault prevention mechanism. The UEC algorithm is based on the equal energy distribution among clusters, whereas the PBC focus on the mapping of CH according to the cluster population. The UEC algorithm performance has been compared against Low Energy Adaptive Clustering Hierarchy (LEACH) and Stable Election Protocol (SEP), whereas the PBC algorithm performance has been compared against Virtual Area Partition-Energy (VAP-E) and Energy-Aware Multi-Hop Multi-Path Hierarchical (EAMMH) protocols. The results of our simulation prove that both UEC and PBC protocols perform better than their ancestors. The deep literature survey concludes that there are two major proven methodologies exist for energy management that are (i) clustering and (ii) routing [3]. Sensitivity: Here, the term sensitivity defines the impact of consequences that occurs due to fault occurrence. The use of sensors is very common in a modern digitised era where everything eventually accommodated with sensors. When these sensors get fail because of any reason it generates some level of impact on the overall performance and design of the system. The consequences of faults can be gauged by various factors such as time, money, effort. On the basis of this, we have been proposed a unique sensitivity based taxonomy in Section 3. Clustering: Cluster formation is an essential part of the routing mechanism. The cluster may form with homogeneous or heterogeneous SNs. The objective behind clustering is as the SNs are limited with energy, therefore, the direct communication with BS is not suitable by considering efficient energy management. Normally, each cluster is controlled by a dominated CH node, which is responsible for regulating the cluster members (CMs) and additionally performs data collection & aggregation operation [4]. The details about various clustering technologies can be found in [5, 6]. Routing: Routing is a best practice adopted by clusters of WSN to select appropriate CH and to choose t...

show abstract

Section: Results Discussionmentioning

confidence: 99%

Fault‐tolerant mechanism for wireless sensor network

Mohapatra

Rath

2020

IET wirel. sens. syst.

Self Cite

View full text Add to dashboard Cite

show abstract

“…And the second part of execution is responsible for cluster formation by measuring the INN gap which is based on nature-inspired phenomena [23][24][25] . Our proposed procedure advocates against the adopted sub-operations by our existing traditional algorithms LEACH and SEP.…”

Section: Smart Water Solution For Monitoring Of Water Usage Based On Weather Conditionmentioning

confidence: 99%

Smart Water Solution for Monitoring of Water Usage Based on Weather Condition

2020

IJETER

View full text Add to dashboard Cite

Conservation of water in urban areas is an ongoing challenge in which technology like IoT and WSN is playing a very crucial role. Studies show that 54% of India is facing absolute water scarcity or high economic water stress. To address this challenge the forecasting and monitoring of water consumption along with effective management and distribution are important. This paper implements the seasonal threshold constraint on water distribution which conserves a significant amount of water loss over uniform supply around the year by considering end-user behavior changes according to the season. The results have been confirmed through simulation of the proposed algorithm Weather-based Smart Water Monitoring (WSWM). This extensive study only suggests a possible alternative approach to design the water distribution system to conserve water. However, more work is required for achieving an optimized approach for sustainable urban water management.

show abstract

“…Sensor noise extracted from images can also be served as the camera fingerprint and this can be done using an approach suggested by Chang-Tsun Li [32,33] were in he proposed the use of an SPN Enhancer which provides an increased rate of device identification. So keeping that in mind we use a defense in depth approach by firstly using the method proposed and also chaining it with some of the operational mitigation which I suppose would be a solution for the problems mentioned above.…”

Section: Literature Reviewmentioning

confidence: 99%

Anti-Forensics: Countering Sensor Noise Camera Identification

Suvarna¹

2020

EPRA

View full text Add to dashboard Cite

In simple terms, Anti-Forensics can be told as the techniques used to counter forensic analysis done by forensic investigators. This paper mainly focuses on some of the most used anti-forensics techniques along with the challenges the forensics investigator faces. There are many tools and techniques available that when used properly can be highly effective against the forensic analysis techniques. Various tools assist you against various anti-forensics techniques like Elimination of evidence source, Data hiding, and Trail obfuscation. These techniques are used mainly to make the investigation consume more time and money. Sensor Noise Camera Identification is a way to link a photo with the camera the photo was taken from using a noise signature that is unique for every camera. KEYWORDS: Anti-Forensics (AF), Forensic Analysis, Anti-Forensic Techniques, Sensor Noise Camera Identification

show abstract

Detection and avoidance of water loss through municipality taps in India by using smart taps and ICT

Cited by 35 publications

References 17 publications

Fault‐tolerant mechanism for wireless sensor network

Fault‐tolerant mechanism for wireless sensor network

Smart Water Solution for Monitoring of Water Usage Based on Weather Condition

Anti-Forensics: Countering Sensor Noise Camera Identification

Contact Info

Product

Resources

About