An increasing interest is drawn to environmental monitoring applications such as weather monitoring, smart city, and smart agriculture. This paper proposes a new Internet of Things (IoT) sensing system for environmental monitoring. The system consists of wireless sensor nodes, communication network, and data visualization and storage cloud. The wireless sensor node is powered by a solar panel and Radio Frequency (RF) energy harvester (in case solar energy is not available) to avoid changing batteries frequently and save the maintenance cost. It has a compact size and can sense many environmental parameters, such as temperature, air pressure, humidity, loudness, and air quality. A low power communication technology named LoRaWAN is used to connect different sensor nodes for a wide coverage area. Finally, a cloud server named Cayenne myDevice is employed to receive, present and store measured data. This smart sensing system with energy harvester can be used for many other IoT applications.

A New Smart Sensing System Using LoRaWAN for Environmental Monitoring

At present, the agriculture sector is moving towards smart agriculture for the proper crop and land management such as minimizing the use of irrigation water and the temperature in a greenhouse among many others. In agricultural fields, either outdoor or indoor, monitoring real-time weather is an important tool. A novel, handheld palmtop weather station that can measure ambient environmental parameters such as air temperature, humidity, barometric pressure, dew point, soil moisture level, and carbon monoxide in the atmosphere with high precision was developed and discussed in this paper. The device comprises an ATMEGA 2560 Microcontroller, a sensor panel, a power unit with rechargeable and removable batteries, an LCD display, and local and cloud storage with a customized web portal. An ergonomic cover was also designed for the device with a micro-USB charging port and a common port to connect external modular sensors such as a soil moisture sensor. As the device is an IoT-enabled device, the user can upload real-time data into a customized website with the location. Sensor accuracy tests were carried out for temperature and humidity with the available reference instruments and the response time of the device was also tested as it affects the performance of the device.

Real-Time Weather Monitoring and IoT-Based Palmtop Device for Smart Agriculture

At present, the recognition of weather phenomena mainly depends on the weather sensors and the weather radar. However, large-scale deployment of meteorological observation equipment for intensive weather monitoring is difficult because it is expensive and difficult to maintain. Moreover, convolutional neural networks (CNNs) can also be used to identify weather phenomena, but existing methods require high computing power of equipment, making it difficult to deploy in practice. Therefore, designing a lightweight model that can be deployed in a small device with weak computing power is crucial for intensive weather monitoring. In this paper, we study the shortcomings of some existing lightweight models. By comparing the disadvantages of these models, a new lightweight model is proposed. In addition, considering the number of existing weather datasets are too small to meet real monitoring needs, so we produced a dataset with a more complex variety of weather phenomena. Through the experiments, the proposed method can save more than 25 times memory usage with only 1.55% accuracy lost compared with the best CNNs method which achieves state-of-the-art performance among the other lightweight models.

Lightweight models for weather identification

Weather is air condition in a certain place and in a relatively short time. Changes in weather can be observed using a device called Automatic Weather Station (AWS). Weather stations measure weather data consisting of temperature, relative humidity, atmospheric pressure, wind speed, light intensity, and others. An online service that provides weather data, one of which is OpenWeatherMap. Weather data from OpenWeatherMap in this study was implemented in a room using an instrumentation system, so that the weather conditions in the room are in accordance with the weather data conditions obtained from OpenWeatherMap. To validate between weather data in a room obtained through sensors against weather data obtained from OpenWeatherMap, the data is processed in a microcontroller. The sensor module used consists of a DHT22 sensor to measure temperature and humidity, a BMP180 sensor to measure pressure and wind speed, and a BH1750 sensor to measure light intensity. To get the same weather data conditions between weather data in a room and weather data obtained from OpenWeatherMap, use an actuator that functions as a weather conditioner in a room. The actuators used consist of heaters and coolers to produce temperature, water spray to produce humidity, fans to produce wind speed, and light bulbs to produce light intensity. The results of this study are prototype weather conditioners in a room based on weather data in a city obtained from OpenWeatherMap.

Implementation of Weather Station for The Weather Reality In A Room

Measuring accurate rainfall at a given area is often essential to agriculture. Farmers in Bangladesh do not have reliable rainfall data very much. Therefore, they are still enduring an immense loss of their crop. The previous year’s rainfall data will also provide vital knowledge for predicting rainfall. The accessible rain gauge in the market is mostly costly and thus not sustainable for farmers. In view of this, this paper aims to design and implement a low cost rain gauge that can quantify the amount of rainfall in a given region with industry standard precision. Around the same time, the retrieved data is stored on an online archive so that everyone can view the former and existing data. As a result, the estimate of rainfall will be eased based on the data stored.

Design and Implementation of a Low-Cost IoT Based Tipping Bucket Rain Gauge

Weather estimate, in reality continuous weather gauge is essential for our day by day life particularly in agribusiness. National weather data does not generally contain the precise information of each area rather it contains the information of closest climate station for a timeframe. The fundamental aim of this project is to develop a RES powered Weather Station which will help to monitor the weather parameters. Such a project contains sensors for detecting temperature, humidity, raindrop, carbon mono-oxide, smoke, LPG in the environment, barometric pressure, altitude etc. The information from the sensors are gathered by the Arduino. Arduino sends the sensors information in LCD display. Additionally, the device sends an SMS which contains weather information to the user with the assistance of a GSM module. At the end of the project the results have been compared between the national weather data and the actual reading. According to the results, the percentage of deviation for Temperature is 1%, Humidity is 5% and Barometric Pressure is 8%.

Md. Hasanur Rahman

Papers

Renewable Powered Portable Weather Update Station