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Internet of Things (IoT) and artificial intelligence are two leading technologies that bought revolution to each and every field of humans using in daily life by making everything smarter than ever. IoT leads to a network of things which creates a self-configuring network. Improving farm productivity is essential to meet the rapidly growing demand for food. In this chapter, the authors have introduced a smart greenhouse by integration of two leading technologies in the market (i.e., Machine Learning and IoT). In proposed model, several sensors are used for data collection and managing the environment of greenhouse. The idea is to propose an IoT and Machine Learning based smart nursery that helps in healthy growing and monitoring of the seed. The structure will be a dome-like structure for observation and isolation of an egg with various sensors like pressure, humidity, temperature, light, moisture, conductivity, air quality, etc. to monitor the nursery internal environment and maintain the control and flow of water and other minerals inside the nursery. The nursery will have a solar panel from which it stores the electricity generated from the sun, a small fan to control the flow of air and pressure. A camera will also be equipped inside the nursery that will use computer vision technology to monitor the health of the plant and will be trained on the past data to notify the user if the plant is diseased or need attention.

This chapter presents the Smart Irrigation system using the Internet of Things (IoT). IoT Technology is a network of physical objects that are connected with sensors, software, etc. This chapter concludes the project based on the agriculture field that automates the irrigation process and on the agriculture field that automates the irrigation process and solves the challenge of water consumption in those areas. We have developed the system using different sensors like (1) Soil Moisture sensor, which measures the moisture present in the soil, (2) Humidity and Temperature Sensor (DHT11), which traces the temperature change. All these sensors are connected to the Node MCU ESP8266 microcontroller, which is also a Wi-Fi module. It uploads the data to the cloud and displays it in the form of readings detected by the Blynk Application. This sensor's reading values control the pump for emergency purposes, such as stopping the pump for irrigation. Thus, this project can automate the irrigation process by analyzing soil moisture and climatic conditions, covering essential aspects like less labor, power consumption, reliability, and cost.

Purpose – The purpose of this paper is to develop prototype of the web-based home fire early warning system using Wiznet W5500 Ethernet module. This system protocol helps users in sending information of fire through the internet with the internet of things (IoT) method using Wiznet Ethernet module as communication media to the user.

Design/Methodology/Approach – This paper presents the design of web-based home fire early warning system using Wiznet W5500 Ethernet module. The system prototype is built using flame sensors, MQ-02 smoke sensors, and LM35 temperature sensors as input components. While on the processor side using Arduino Uno microcontroller as sensor data processing. Processed data is sent to the Ethernet module as a web server resulting in a web-based early warning information system with an alarm notification on the browser along with home location status information and sensor data.

Findings – This research produces a prototype of the web-based home fire early warning system using Wiznet W5500 Ethernet module that has been able to provide notification to the security officer housing.

Research Limitations/Implications – In the implementation of measurement, the information system only accesses one house detector or one fire location.

Practical Implications – This research produces a prototype of the web-based home fire early warning system using Wiznet W5500 Ethernet module that has been able to distribute data of temperature, smoke, and fire.

Originality/Value – The development of fire monitoring systems using flame sensors, smoke sensors and integrated temperature sensors in internet-based communication systems of things via the Internet W5500 does not appear to have been published yet.

In this chapter, an attempt has been made to develop a security-based hardware system using an 8-bit single-chip microcontroller in conjunction with some sensor technology and lighting and alarming actuators. The proposed system aims to ensure the security and privacy of a dedicated area in terms of unauthorized human intrusion, hazardous gas leakage, extreme prolonged temperature changes, atypical smoke or vapor content in space and abrupt drop in illumination. The proposed system is capable of detecting any type of physical intervention and hazardous anomalies in the environment of the reserved space. In order to define the operation of the system, programs written in C++ with the special rule of code structuring have been deployed on the microcontroller using the Arduino Integrated Development Environment. The system is like a small container, enclosing all the respective sensor modules, microcontroller board and open connections for actuators. The proposed system is easy to use hardware and does not demand any human intervention for its functioning and can be installed with almost no changes in the infrastructure.

The impact of mitigating flood occurrence in the rural and urban areas has become crucial as it has affected government policies for countries that are prone to flood disaster. Efforts and funds have been put up to a higher level of capabilities to ensure that coping and managing flood disaster could be resolved. Several initiatives made in managing flood are: effectively monitoring the potential at-risk inundated area, improving the river water irrigation and drainage and undertaking the environmental pollution. This chapter basically focusses more on the improvement of flood monitoring system device at the potential flood area. The approach of ubiquitous mobile SCADA offers a low-cost, portable, and small in size flood monitoring system device with easily accessible data. An easy web monitoring of environment surrounding anywhere and at any time offers a real-time data updated with a very minimum delay of each and every environment data required. There are several sensors like ultrasonic, sound, temperature and humidity, water drop and vibration sensors are equipped together with one small monitoring system platform. The alert of water level condition is notified through a beeping buzzer and light LED notation of various colors of green, yellow and red, which notify any increase of water exceeded. The platform is powered by a rechargeable battery that allows the platform to be mobile and portable. Hence, flood monitoring system platform promotes a low-cost, easy-to-handle and ubiquitous data updated device for a better monitoring system platform.

The United Nations (UN) adopted Sustainable Development Goals (SDGs); agenda 2030 focuses on Climate Action (goal 13), targeting climate adaptability, as well as resilience, awareness and improving policy mechanisms on climate change. In order to enhance climate adaptability, climate-smart agricultural practices (CSAP) is a necessary step. CSAP is a sustainable agriculture approach with a strong focus on climate dimensions. The three pillars of climate-smart agriculture (CSA) are ‘Adaptation’: adapting to climate change; ‘Resilience’: building resilience against it and ‘Remove’: reducing carbon emissions. The new world economy uses Industry 4.0 technologies for sustainable advancement, including blockchain technology, big data analytics, artificial intelligence (AI), augmented and virtual reality, industrial Internet of Things (IoT) and services. Hence, technology plays a significant role in climate sustainable agriculture practices. This chapter shall consider three technologies consisting of IoT, AI and blockchain technology which contribute to CSAP in pre-harvesting (monitoring climate as well as fertility status, soil testing, etc.), harvesting (tilling, fertilisation, seed operations, etc.) and post-harvesting (predicting weather factors, seed varieties, etc.) periods of agriculture. All these three technologies work like the human nervous system; IoT helps in converting various information regarding demography, climate change, local agricultural needs, etc. into world data; AI works like a brain in combination with IoT, helps predict the use of climate-smart technology and blockchain, the memory part of the nervous system which deals with supply-side and ensures traceability as well as transparency for consumers as well as farmers. Hence, this chapter shall contribute to the importance of these three technologies in adopting CSAP in three stages of agriculture.