Modernizing fish ponds for agricultural production face major challenges in terms of capital expenditure and operational expenses. Fish farming of particular types of fish species necessitates the fulfilment of several requirements because, like several other living organisms, fish have a precise limit for an assortment of environmental criteria. For the good health and development of the organisms, big farms typically have certain kinds of water surveillance and replacement mechanization systems. To preserve the ecosystems for living fish, the people who work in the fish farming ponds must be active throughout the day. Local farmers who operate on relatively small ponds couldn't afford to compensate employees to manage daily tasks, which typically include keeping an eye on water levels, temperature, and pH levels. As a result, the prime motive for this paper is to monitor and take steps to keep the habitat's eco-friendly environment for specific species of fish, which will decrease the time required for some basic actions. This article puts forth a smart Internet of Things (IoT) based fish pond water monitoring system. Such a smart system consists of several real-time sensors that monitor and send inputs to a microcontroller and the data is stored in a real-time database. The user can track these values through a phone app that is assimilated with the cloud by having them transmitted to the cloud at periodic intervals and this helps the fish pond owners to take required action quickly and effectively when needed. As embedding devices are typically made up of an Arduino board, internet and relay frames, and a computer interface, a farmer could easily source these parts. With the help of this integration system, farmers can reduce operating costs and boost overall effectiveness by avoiding the need to hire employees for their location.
The quality of service (QoS) is the general estimation of the execution in the organization. The sprouting constant gives quality of service (QoS) support in remote and portable systems administration conditions. The QoS can't be given a penny rate yet the better execution can be given the thought of the measurements. Later Wireless Networks support remote access for versatile specialized gadgets by giving a remote connection point between the cell phones and a proper organization of restricted range base-stations (BS). Based on the foundation model for remote interchanges, the air-interface comprises a solitary information connection ending on a Base Station. Correspondence starting there is directed across a fixed organization to its objective. Portability is overseen by allotting a restricted arrangement of correspondence recurrence channels to every BS, and progressively doling out a portable gadget to a neighborhood channel as it moves from the inclusion area of one BS to another. While giving QoS in an infrastructure climate is troublesome, supporting QoS in portable specially appointed networks, which don't rely upon a BS for correspondences, is significantly more troublesome. Basically, a portable specially appointed network is an organization of versatile switches.
In this paper, An EEG-based home automation and anomaly detection of physically challenged people has been designed using Neurosky Mind wave headset. This project has been implemented to make the automation easier and to detect abnormality of physically challenged people. The operation involves by collecting average thoughts in different states of mind as EEG (Electroencephalogram) waves using neurosky headset which has three electrodes connected to ear lobe and frontal lobe of the brain. The collected data are processed by a Brain Wave Automation/Anomaly Detection algorithm (BWAD) of each state like meditation, attention and eye blink using Raspberry pi. Based on the calibration of processed data are used to actuate the electronic appliances as well as to find the abnormality of physically challenged/impaired people.
The main aim of this work is to implement a progressive path-planning algorithm with a proposed hybrid network based CNC-C (Cooperative Network Coded–Communication) architecture for a smart evacuation system. An algorithm ALCDTS (Health based Age–Length–Capacity–Distance–Trustiness–Speed) is proposed to generate possible progressive routes by considering the building conditions, hazard estimation, path capacity along with the occupant’s age, speed and health status. The investigation of ALCDTS is carried out by using the path finder simulator. The comparative study between the conventional evacuation algorithm and ALCDTS algorithm has been performed and the results are obtained. A four-storied shopping mall is taken as a building model where the performance of test cases for abnormal event is analysed.
Vital Health monitoring of aged people without help of technologies is quite a difficult task. Because when the measures are done manually, there is all-time need of caretaker with the elderly people. This can be overcome with the help of health and activity monitoring system with many new technologies. Wireless infrastructure can support current and emerging technologies. Despite of executing the activity by such a centralized server, the device comprises a disseminating centralised system. The proposed health and activity monitoring system consists of a wearable sensor node and deployed sensor node, which is interfaced with the IOT architecture. An analysis is carried out using BPAD (Body Parameter Abnormality Detection) algorithm to detect any deviation in the health condition of the person. The smart phone API (API refers as application processing interaction) accesses the database of centralized server.
This paper proposes a fault detection system designed for transmission lines using Long-Range Wireless Sensor Network (LoRAWSN). The system is designed to detect and locate faults across transmission lines in real-time, which can significantly improve the reliability and efficiency of power transmission systems. A WSN will be built across transmission lines over an area. The faults identified by these sensor nodes is then transmitted to a central control unit, which analyses and displays the data. The LoRaWAN technology enables the WSN to cover long distances while consuming minimal power, making it ideal for monitoring transmission lines. The proposed fault detection system is evaluated through real world experiments, which demonstrate the feasibility and effectiveness of the proposed system. Overall, this paper presents a novel and practical approach for fault detection on transmission lines, which has the potential to improve the reliability and efficiency of power transmission systems.
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