scispace - formally typeset
Search or ask a question
Author

Shridevi Subramanian

Bio: Shridevi Subramanian is an academic researcher. The author has contributed to research in topics: Semantic interoperability & Interoperability. The author has co-authored 1 publications.

Papers
More filters
Book ChapterDOI
10 Oct 2017
TL;DR: In this article, the authors introduce the key concepts in the semantic technology domain and key business applications in Internet of Things (IoT), and cover the emerging ontologies such as semantic sensor networks (SSN) and IoT and the impact they will have on IoT smart solutions and future collaborative interoperable applications.
Abstract: This chapter introduces the key concepts in the semantic technology domain and key business applications in Internet of Things (IoT). It covers the emerging ontologies such as semantic sensor networks (SSN) and IoT and the impact they will have on IoT smart solutions and future collaborative interoperable applications. Ontologies and alternative semantic technologies are often key enabling technologies for sensor networks, as they facilitate semantic interoperability and integration, reasoning, classification, different kinds of assurance, and automation not addressed within the OGC standards. Semantic sensor networks work on the interoperability of physical sensor networks to ease the sensor discovery. The chapter examines evolving standards and consortiums that were instigated to advance standardization work and interoperability of IoT. It presents final remarks using a case study and guidelines to encourage readers to innovate and build differentiated solution that contributes toward refining the quality of lives and smart business practices in the domain of IoT.
Proceedings ArticleDOI
14 Jun 2023
TL;DR: In this article , the authors proposed a real-time air quality monitoring system using an MQ2 sensor and ESP32 microcontroller, which can detect the concentration of pollutants in the air to classify whether it is fresh or poor air.
Abstract: The air is an essential aspect of humans’ daily lives as it helps in breathing. With the rise of air pollution, it is necessary to have an efficient air quality monitoring system that can detect the concentration of pollutants in the air. In this study, the design and implementation of air quality monitoring system is discussed which uses an MQ2 sensor and ESP32 microcontroller. The system detects the ppm levels in the air to classify whether it is fresh or poor air. The challenges include establishing reliable connectivity, visualizing data effectively, integrating multiple sensors, ensuring accurate measurements, and enabling real-time analysis. The ESP32 microcontroller addresses connectivity issues by providing built-in Wi-Fi and Bluetooth capabilities. The LCD display offers real-time visual feedback, enhancing data visualization. Integration of the DHT11 sensor for temperature and humidity measurement and the MQ2 sensor for gas detection enables comprehensive air quality monitoring. The ThingSpeak application acts as a cloud-based IoT platform, allowing data logging, remote monitoring, and real-time alerts and notifications. If the ppm levels are less than 1000, it is considered poor air, and a buzzer is triggered, along with an LCD I2C display that shows the levels using the I2C protocol. The system also uses a DHT11 sensor to detect temperature and humidity and passes all data to the cloud channel by using IoT, triggering a mail alert using Google sheet with an on and off button for ppm levels using Javascript extension and GPS. The system is designed to provide a real-time solution for monitoring air quality, making it an essential tool for public health and environmental protection.