Damini Lightning Alert App Download

Lightning is one of the scariest natural phenomenons. It can kill a person or cause wildfires with a simple strike. It would be great if there's a way of knowing when and where exactly lightning will strike but so far there's no technology for that yet.

But with this app, although it can't predict exactly when and where, it will notify you if there are active thunder storms near your area. That way, you can avoid going to those places. Or if you live in the area, you can take precautionary measures to avoid the lightning strikes.

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Despite State and national-level action plans to mitigate risks posed by lightning strikes, the country witnessed a record number of deaths due to lightning in 2022. According to data available with the Ministry of Earth Science, as many as 907 people were killed till November 2022 after lightning struck them, a leading cause of death from natural disasters in the country. This is the highest death toll due to lightning in the last 14 years in India.

A total of 2,183 people were killed across the country in 2022 due to various extreme weather events, such as heatwaves, cold waves, cyclones, lightning, heavy rainfall, and landslides. Among the various disastrous weather events, floods induced by heavy rainfall claimed the lives of around 804 people, the second highest natural disaster event after lightning.

Monsoon season account for the maximum number of annual total lightning flash counts in India with around 47.2% followed by summer (41.5%) and post-monsoon season (7.7%). The observed higher magnitude of lightning flash count across India during April-June also indicates the unstable atmospheric conditions and the resultant electrical vigour over the Indian region. The overall fatality rate is also about 0.25 per million per year in India, says the study.

The app monitors lightning occurrences all over India and alerts the user of lightning near them by a GPS notification under 20 km and 40 km. Further, the Damini App also triggers warnings about lightning strikes one or two hours in advance.

Damini Lightning Alert application is for giving warning to the user about the lightning on the basis of user location. Users can view lightning which occurred in the last 5 min, 10 min and 15 min on the map.

The sensor sends a warning half an hour before the lightning strikes. The network has sensors connected to the Central Processing Unit at IITM. Therefore, citizens will get live updates and accurate forecasts of thunderstorms and lightning strikes while at home.

My Lightning Tracker is a free app for Android devices that will notify you of any nearby lightning strikes. It's a useful tool to have on your phone, especially if you live in an area where thunderstorms are a common occurrence.

The lightning annual report also says that the main causes of lightning deaths are due to standing under tree, direct hit, and indirect hit. The percentage of lightning deaths due to primary causes is shown in Figure 4. Tribal people that live in close proximity to nature are more susceptible to lightning strikes since they occur more frequently in open spaces, rainforests, and bodies of water. Their homes have thatched or katcha roofs, making them vulnerable to lightning strikes.

People are still impacted by the lightning issue and have been powerless to solve it. Although many studies have been done to lessen the effects of lightning, the physics behind it is still not fully understood. Several countries have established lightning awareness cells and lightning research centers, which are engaged in research and awareness raising [6]. In India, only a few states like Andhra Pradesh, Assam, Bihar, Karnataka, Odisha, and West Bengal have expensive lightning alert systems. These states are MoU with Earth Network for weather and lightning data. Lightning losses are attributable to a lack of understanding or a communication gap that does not enable last-mile connectivity. According to the survey, tribal members and farmers involved in the field are most at risk of being struck by lightning in rural areas. The majority of recorded lightning-related deaths involved people who were standing beneath large trees. So, there is a need to develop a low-cost lightning/weather alert system in rural areas to alert and creates awareness in advance about lightning/thunder storm through multiple alerting methods. The suggested system will eventually be trained to spot lightning and dangerous weather conditions in advance using AI and to warn rural people of these conditions.

The death rate from lightning is reportedly four times higher in South Africa than it is globally. Rural areas remain at risk and carry on without receiving any lightning warnings despite major advancements in lightning monitoring and detection on a national level. A community-based alert system was built by Mahomed et al. [17] to identify and communicate lightning risks and alerts in Swayimane, KwaZulu-Natal, South Africa. This system consists of an electrical field meter and a lightning flash sensor, and it sends out email and SMS notifications as well as loud and visible alarms locally to notify people of impending danger. Earth Networks contribute to national, state, and municipal efforts to minimize lightning deaths, injuries, and damage throughout India by deploying and operating national total lightning detection networks and supporting stakeholders with much-needed data and analytics. Geospatial, SMS, and IoT-based lightning alert systems are presently existing to alert people about lightning/critical weather conditions. These alert methods are not reaching the rural people due to lack of the literature and poor network facilities. Nerella and Ahmed [18] proposed a low cost an AIoT-based lightning alert system to alert rural people in advance about lightning based on weather prediction to reduce lightning disaster.

Intriguing answers to problems in embedded and IoT applications are provided by LoRa, a low-data-rate, long-range wireless technology. It used little electricity and allowed data to be obtained from various sensors at remote locations [19]. Nerella and Ahmed [20] developed a weather monitoring and lightning alert system based on LoRa and IoT technology. This system overcome the limitations of IoT-based lightning alert system by using LoRa communication. Weather sensors, lightning detector, ESP32, LoRa module, gateway, and ThingSpeak platform are the components to make the system is IoT enabled. Dharani et al. [21] developed a system with the goal of rescuing and defending fishermen from calamities and border crossing. This prototype is built using GPS tracker, lightning detector, GSM module, MCU, LEDs, and buzzers, it alerts the coast guard and fishermen about severe weather conditions and border crossing through SMS and sirens.

There are three fundamental techniques for predicting lightning and warning people: SMS, IoT, and geospatial-based systems. These expensive lightning warning systems are installed in a few states, and with the help of the Earth Network Data and State Disaster Management Authority and alerts are sent via SMS, mobile apps, and television channels. Rural residents are still hard to reach despite these efforts to warn them due to inadequate network infrastructure, illiteracy, and ignorance of lightning-related mobile apps. The proposed system is one more way to get around these constraints. A comparison between the proposed and existing alert systems is described in Table 1.

Here, various alerting methods are introduced to alert the rural people about the weather and lightning. They are announcement, siren, voice call, Bluetooth, WhatsApp, email, SMS, mobile Apps, etc. IoT- and LoRa-based weather and lightning alert system is shown in Figure 5. ESP32, various nanosensors, LoRa module, Lightning Detector-AS3935, speakers, gateway module, cloud platforms, smartphone, and client systems are the basic building blocks of lightning alert system. Basically, a nanosensor is very sensitive device which is shielded precisely within the detectors. In this work, various nanosensors are used to monitor the weather parameters.

IoT-based lightning/weather alert ecosystem in rural areas is shown in Figure 6. Weather stations, gateway, wireless-based announcement system, cloud platforms, mobile users, authorized persons, and rural people are in the part of this ecosystem. Here, gateway module receives data from various weather stations and processes the received data. If weather conditions are abnormal, it sends lightning alerts and lightning safety awareness information to government officials/rural communities/nobile users/rural people through various alert methods using various cloud platforms, IoT, and LoRa technology for reducing lightning disaster.

Prototype of wireless-based weather announcement module is shown in Figure 9. Arduino nano, LoRa-based gateway module, SD card module, speakers, and buzzer are the building blocks of announcement module. The gateway module receives weather information from weather station and sends the real-time weather sensors data to the announcement module. Announcement module processes the received data frame, announce the live weather/lightning information with the help of the speakers and it also creates the awareness to rural people about lightning/critical weather conditions in advance.

(i)Work on various modules like lightning detector, weather sensors (DHT sensor, pressure sensor, anemometer sensor, rain sensors, etc.), LoRa module, GPS module, ESP32, and lightning emulator.(ii)Implementation of IoT-based weather monitoring and lightning alert system in rural areas using LoRa technology.(iii)Design and development of weather stations, gateways, and announcement systems to alert the rural people through various alert methods.(iv)Study of various existing machine learning algorithms on weather and lightning forecasting and look into implementation of proposed system.

Since the Arduino IDE platform has the capabilities to support large libraries, a sizable community, and simple to integrate the board packages in it, we chose it to construct the lightning/weather alert system. Here, Arduino programming is used to implement the functionality of weather stations, gateways, and announcement system. An algorithm for a weather station is explained in Algorithm 1 and implementation of gateway functionalities are described in Algorithm 2 and 3. Algorithm to implement announcement system functionality is explained in Algorithm 4. 2351a5e196