Smart Home Automation-cum Agriculture System

Katangle, Shubham; Kharade, Mayuresh; Deosarkar, S. B.; Kale, Ganesh M.; Nalbalwar, Sanjay L.

doi:10.1109/i4tech48345.2020.9102688

Cited by 6 publications

(3 citation statements)

References 17 publications

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“…It enables home automation via voice commands through Google Assistant and IFTTT integration and offers agricultural monitoring with soil moisture, temperature, and humidity analysis. The system efficiently manages water flow based on soil conditions and utilizes Wi-Fi for data transfer to cloud storage (Thingspeak) and the Blynk IoT platform [25,26].…”

Section: Related Workmentioning

confidence: 99%

Design and Implementation of Internet of Things (IoT) Platform Targeted for Smallholder Farmers: From Nepal Perspective

Lamsal,

Karthikeyan,

Otero

et al. 2023

Agriculture

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Nepal, a lower-middle-income country in South Asia, predominantly features smallholder farming communities operating on modest land holdings. These smallholders often adhere to traditional farming methods, relying on familial labor, which has become increasingly inefficient in contemporary agricultural landscapes. To enhance their productivity and efficiency, smallholder farmers require affordable and accessible Internet of Things (IoT)-based systems. However, the prevailing IoT solutions in the market primarily cater to large-scale commercial enterprises, rendering them unsuitable for the specific needs and constraints faced by smallholder farmers. In response to this gap, we have introduced a cost-effective, customizable, scalable, and dependable IoT platform tailored expressly for smallholder farmers. This platform empowers them to visualize, monitor, and control real-time data pertaining to their crops, livestock, and other agricultural assets. To ascertain the efficacy and suitability of our proposed platform, we conducted a comparative analysis with existing counterparts such as Blynk IoT and ThingSpeak IoT, evaluating their respective features and application services against standard requirements. Additionally, we subjected our platform to rigorous server load testing, assessing crucial performance parameters including throughput, response time, user capacity, and data sampling rates. Over an observation period spanning an average of 339 days, our platform successfully processed and stored a substantial volume of data, encompassing 817,633 sensor messages, averaging 2412 messages per day, with a cumulative storage size of 14,238.28 KB. Extrapolating from these results, it is noteworthy that an A0 instance with 20 GB of cloud space can adequately accommodate 200 users at a rate of 100 MB per user, which is adequate for the smallholder needs. Furthermore, the purposed platform was deployed inside a polyhouse to perform off-season grafting of citrus plants. The achieved success rate of 84% closely approached the success rate of 90–95% observed during on-season grafting. These empirical findings, coupled with the extensive data gathered during our research, underscore the reliability and performance of our proposed IoT platform for smallholder farmers.

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Section: Related Workmentioning

confidence: 99%

Design and Implementation of Internet of Things (IoT) Platform Targeted for Smallholder Farmers: From Nepal Perspective

Lamsal,

Karthikeyan,

Otero

et al. 2023

Agriculture

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“…Those voice commands should first be interpreted using speech recognition. Speech recognition has been used in many fields, including medicine [2], agriculture [3], smart homes [4], and smart vehicles [5]. Research suggests that by 2022, nearly three-quarters (73%) of drivers will use speech recognition technology [6].…”

Section: Introductionmentioning

confidence: 99%

LimitAccess: on-device TinyML based robust speech recognition and age classification

Maayah

Abunada

Al-Janahi

et al. 2023

Discov Artif Intell

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Automakers from Honda to Lamborghini are incorporating voice interaction technology into their vehicles to improve the user experience and offer value-added services. Speech recognition systems are a key component of smart cars, enhancing convenience and safety for drivers and passengers. In the future, safety-critical features may rely on speech recognition, but this raises concerns about children accessing such services. To address this issue, the LimitAccess system is proposed, which uses TinyML for age classification and helps parents limit children’s access to critical speech recognition services. This study employs a lite convolutional neural network (CNN) model for two different reasons: First, CNN showed superior accuracy compared to other audio classification models for age classification problems. Second, the lite model will be integrated into a microcontroller to meet its limited resource requirements. To train and evaluate our model, we created a dataset that included child and adult voices of the keyword “open”. The system approach categorizes voices into age groups (child, adult) and then utilizes that categorization to grant access to a car. The robustness of the model was enhanced by adding a new class (recordings) to the dataset, which enabled our system to detect replay and synthetic voice attacks. If an adult voice is detected, access to start the car will be granted. However, if a child’s voice or a recording is detected, the system will display a warning message that educates the child about the dangers and consequences of the improper use of a car. Arduino Nano 33 BLE sensing was our embedded device of choice for integrating our trained, optimized model. Our system achieved an overall F1 score of 87.7% and 85.89% accuracy. LimitAccess detected replay and synthetic voice attacks with an 88% F1 score.

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“…The Arduino microcontroller is a versatile device capable of receiving input, executing programmed instructions, and generating outputs as required [8]. These outputs may include measurements of air [9] and soil moisture [10], among other possibilities. One of the existing technologies involves the utilization of an automation system that employs a microcontroller for the purpose of automatically regulating the water pump [11].…”

Section: Introductionmentioning

confidence: 99%

The Implementation of Smart Home Monitoring Systems for Real-Time Water Level Measurement, in Combination with the Internet of Things (IoT), presents a Potential Pathway for Attaining Energy Efficiency in the Realm of Electricity Consumption

Gowthaman,

Arulmozhi

2023

IJRASET

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Water pumps play a crucial role in facilitating the provision of water for various domestic activities. Nevertheless, the energy consumption necessary for its operation is substantial. Prior studies have investigated the implementation of an automation system utilizing an Arduino microcontroller to conserve electrical energy in a water pump. This system was designed for the purpose of automating plant watering and incorporated ultrasonic sensors to mitigate the risk of overfilling. The present study introduces an affordable Smart Home Monitoring (SHM) system. The current automation system can be enhanced through the incorporation of a water sensor. This addition aims to mitigate the occurrence of vacuum and excessive water in the tank, which arises from imprecise water level calculations conducted by the ultrasonic sensor. Furthermore, this study aims to implement an automated water filling system, which allows users to conveniently monitor the remaining water level in real-time through smartphones utilizing the Internet of Things (IoT) technology. Notably, this approach has not been previously explored by researchers. The assessment of energy conservation achieved through the utilization of a water pump is determined to be 39.2% when employing Smart Home Monitoring (SHM) technology

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Smart Home Automation-cum Agriculture System

Cited by 6 publications

References 17 publications

Design and Implementation of Internet of Things (IoT) Platform Targeted for Smallholder Farmers: From Nepal Perspective

Design and Implementation of Internet of Things (IoT) Platform Targeted for Smallholder Farmers: From Nepal Perspective

LimitAccess: on-device TinyML based robust speech recognition and age classification

The Implementation of Smart Home Monitoring Systems for Real-Time Water Level Measurement, in Combination with the Internet of Things (IoT), presents a Potential Pathway for Attaining Energy Efficiency in the Realm of Electricity Consumption

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