Do you know history of Mughal Dynasty?? (Part 1)

-


Mughal Dynasty:  Babar Expedition in Sub-Continent


Babur father, Umar had his realm in Fargana from where Baber took step forward to conquer more relevant territories like Bukhara. Babur was busy in his son, Kamaran in marriage arrangements. During this arrangement, representatives of Dolat Abad, Governor of Lahore and Rana Sanga, Governor of Mewar came for inciting them for battle in Delhi against Ibrahim Lodhi. Babur had already wish in his heart to take step forward toward sub-continent for spreading his kingdom. He prepared his expedition and fought battle of Panipat where Ibrahim got defeat and Babur conquered Delhi and Agra. When Rana Sanga came to know that Babur would not go back from sub-continent after battle then he fought battle of Kanwaha with Babur expedition but got defeat. Before battle of Kanwaha, Babur and his expedition did promise to give up brooze in way of Allah. Babur after getting these enormous victories decided to establish his realm in Delhi. Hamyun and his close companion, Tardi Baig wanted to go back in Kabul as they did not like hot weather of sub-continent. 

Hamayun fell ill and there was no hope of his recovery. Babur prayed for Hamuyun recovery against his life which was accepted as when Hamayun got recovery from illness then Babur fell ill and could not live long. His grave buried in Kabul. 

Babur wrote Babur Nama about his whole life history. He had keen of gardening and liked nature. He knew different language like Arabic, Turk, and other languages.

He spent most of time in conquering more territories in sub-continent which is why he could not give attention toward administration of conquered territories.




Stay with us for next blog on remaining parts of our history...........

Comments

Post a Comment

Please do not enter any spam link in comment box.

Popular posts from this blog

IoT Timeline in Morocco and Insurance Sector

-
Image
  The use of IoT technology in Morocco is still in its early stages, but there have been some notable developments in recent years:   2017: The Moroccan government launched a national plan to develop IoT technology and promote its use in various sectors, including agriculture, industry, and smart cities.   2018: The Moroccan startup scene began to embrace IoT, with companies such as DataCare and Nectarin developing IoT-based solutions for healthcare and agriculture, respectively.   2019: In partnership with the French company Sigfox, the Moroccan telecom operator Inwi launched an IoT network covering more than 80% of the population, making it one of the largest IoT networks in Africa.   2020: The Moroccan government continued to invest in IoT technology, launching initiatives such as the "Smart Agri" program, which aims to use IoT to improve agricultural productivity and sustainability.   Overall, while IoT adoption in Morocco is still relatively low compa
Read more

Machine Learning Algorithms in Agriculture Insurance

-
Machine learning has emerged as a valuable tool in the field of agriculture insurance, offering numerous applications to enhance risk assessment, improve productivity, and streamline processes. Here are some key areas where machine learning is being utilized in agriculture insurance:   Risk Assessment: Machine learning algorithms can analyze historical data on weather patterns, soil conditions, and crop performance to assess the risk associated with insuring agricultural operations. By identifying patterns and correlations in the data, these algorithms can estimate the likelihood of crop failures, diseases, pests, and other risks, helping insurers determine appropriate coverage and premiums.   Crop Yield Predictions: Machine learning models can utilize satellite imagery, weather data, soil information, and historical crop yield data to predict crop yields accurately. These predictions can assist insurers in setting coverage levels and pricing premiums based on expected production
Read more

Machine learning models in Pakistan agricultural data

-
Machine learning model can be applied on agriculture data to facilitate farmers in increasing the productivity. Pakistan is an agricultural country which has major portion in GDP. There is huge gap in this sector which can be fulfilled by adopting technology. Machine learning model can be applied on agriculture relating data to predict the disease or health of crops and to predict the climate change and to examine the impacts of other factors. This model can automate the processing of agriculture productivity. This model will also help the insurance sector to facilitate the farmers timely in case of tragedy or calmity. We need to train our youth in machine learning roles to increase the share of agriculture sector in GDP and economy.
Read more