Data Collection and Storage System in Agriculture Sector
Discuss about the Business Intelligence in Agricultural Analytics for Farm.
The advent of technology within the agricultural sector has been a major boon for the sector. With the advancements in the field of technology, farmers would like to implement the technology within the sector in order to yield better results of agriculture such as better production of crops, high profits for the farmers and better quality of food. The technological and the digital advancements are taking the industry within their grip and has started improving the yield in the sector. It has also added much value within the supply chain of farm to fork (Suprem, Mahalik and Kim 2013). It has also helped in the usage of the natural based resources in an efficient way. The data that could be generated with the help of sensors or agricultural based drones that are collected from the farms or during the transportation of the crops would be helpful in offering information about the seeds, crops, costs, soil or the use of fertilizer and water (Sonka and Ifamr 2014). Several other kinds of technologies such as Internet of Things and advanced analytics could be helpful for farmers in order to analyze real time data such as temperature, prices, moisture content, weather or GPS signals. They also help in providing valuable insights on the optimization and the increase of the yield, improvement of the planning of the farm, making of the smarter decisions about the needed resources and the places of distribution.
This particular report is undertaken to explain data collection and storage system in agricultural sector. This report also discusses about the consumer centric product design, the recommendation system and the processes for the continuity of the business within the sector of agriculture.
Innovations in the field of big data within the agricultural sector and the analysis of management, centers of the analysis of the image, mapping of the plants and the mapping of crops. A predictive based analysis could also be used in order to make smart decisions in the field of farming by the collection of real time data based on the quality of the air and soil conditions, maturity of crops, costs of labor and availability of equipments, weather conditions and many other forms of data. The analysis of the data would be a challenge with the enormous increase in the data size (Lamprinopoulou et al. 2014).
This data would combine in order to assess the level of performance and crop management, operations of the field and soil. Agriculture is regarded as one of the important survival sources. The analytics of big data in the applications of agriculture have provided a greater insight in order to provide advanced decisions on the weather that would affect the farm conditions (Schader et al. 2014). They would also be helpful in yielding the productivity and thus avoid unnecessary cost that would be related to the harvesting and the use of fertilizers and pesticides. Efficient techniques of spatial data are much required in order to gain valuable information from the spatial sets of data. In present conditions, the techniques of spatial data mining are as classification, clustering and association (Shelestov et al. 2013). An effective analysis of the data was performed by using the techniques of hybrid data mining by the mixture of the techniques of classification and clustering.
Big Data Analytics and Spatial Data Mining
In the age of advancing technology, the systems of storage should be designed in such a way that it should be able to handle the agricultural data (Abbasi, Islam and Shaikh 2014). It should be also able to promote the processing of heavy server that would be needed in an efficient cost effective way. The rising need of the forestry inventory and agricultural data has provided the challenge to deliver high quality systems of storage of the data (Channe, Kothari and Kadam 2015). The need for the use of the tools for the analysis of big data is mainly emphasized with the requirement of big data. The real time data could be stored in various kind of servers. The farmers also have the need to gain the valuable information related to their crops and various other aspects related to the agricultural sector. The technology of cloud computing is one of the recent technological trend that could impact the agricultural sector (Bosona and Gebresenbet 2013). The data stored in the cloud infrastructure could be easily accessed by the farmers. The security of food is another major factor, which can help in promoting the widespread adaptation of Information Communication Technology (ICT) within the sector of agriculture (Abdullah and Samah 2013). The tools for ICT that could be used in agriculture include Google Earth engine. They provide the tools and methods of computing based on parallel processing. With the help of this tool, agricultural scientists would be able to collect information that would be time sensitive based on weather and water (Haldane and Antle 2015).
The consumer centric is a kind of activity of the business with the consumer in such a way that it would be able to provide a positive business experience with the consumer before and post-sale to drive business repetitiveness, loyalty among the consumers and incurring more profits (Singh, Keshav and Brecht 2013). The process of consumer centricity is not only limited to the providing service to the consumer. It is also meant to offer greater experience from the stages of awareness through the process of purchasing and after the purchasing has been made. The consumer-centric is a kind of strategy, which is based on the principle of putting the consumer at the topmost priority and the core level of the business (Bogers, Hadar and Bilberg 2016).
Putting the customer at the core of the business model would help in the incurring certain benefits, which could be majorly used to enhance the experience of the customers.
- The use of the data of the consumers would be helpful for the business in order to understand the behavior, engagement of the consumers within the business and the varied interests of the consumers (Spiess et al. 2014).
- With the help of the data, business could help in identifying various opportunities in order to develop services and products for the benefit of the consumers.
- The lifeline value of the consumers could be used in order to segment the consumers based on the value of top spending consumers.
In the recent agricultural trends, the dynamics based on agriculture are changing at a rapid pace (Badia-Melis, Mishra and Ruiz-Garcia 2015). The trend of the agricultural sector would be moving from the methods of traditional farming towards smart farming. The primary goal within the agricultural sector is to improve the productivity within the agricultural sector while meeting the demand of the consumers in order to reduce the varied use of famous pesticides and various kinds of chemicals on the crops. There were many startups and IT organizations that have helped the farmers in order to manage the pests, diseases among the plants, conditions of the weather and yield of supply of crops (Cavallo, Ferrari and Coccia 2015). The tools for analytics and supporting of decisions use the sources of data in order to present recommendations to the consumers. The use of analytics of data would also help in growing more crops. It also helps in fostering loyal relationships with the core customers within the process.
Cloud Computing and ICT Tools like Google Earth
One of the prime causes for the continuous breakdown in the trends of agriculture is the crop cultivation, which is not so suitable with the factor of environment such as weather and the conditions of the soil. The problem could be solved with the help of the Recommendation System (Kumar et al. 2013). It is a kind of system of the filtering of information that would be able to forecast the items that might be some additional interest for the users. The recommendation system could also be helpful in providing various kind of suggestions for a particular kind of crop, which could be cultivated on the basis of the weather and the soil conditions (Moore et al. 2015).
The content-based systems would be able to examine the properties of the various items for the purpose of recommendation. The collaborative systems of filtering would be able to automatically extract the structured form of information from the unstructured form of information or other form of machine readable documents (Nikolidakis et al. 2015).
Every form of business has to prepare for the worst kind of situation, which might arise from the outages of power or any other kind of disasters. The online businesses, which are meant to store the agricultural data of the various farms have to take the responsibility to store the data of the farmers in an efficient way. A proper Disaster Recovery Plan (DRP) should be designed in order to save millions of money (Wallace and Webber 2017).
A proper disaster recovery plan is a kind of plan that is mainly used for the restoration and providing accessibility of the data in the cases of disaster, which could destroy every part of the resources of the business. The job of the DRP is to ensure the happenings in the surroundings such that critical data could be easily recovered within the possible shortest time (Dowd et al. 2014). There are many kind of disasters, which could happen such as natural, man-made or technological disaster such as outages of power. A backup generator could be the primary support in cases of power outages (Castillo 2014). UPS could also be another form of technique to solve the problem in cases of disasters faced by online businesses. These are the kind of battery systems that are particularly designed in order to plug-in such kind of things such as workstations, routers and different kind of servers in the cases of loss of power.
Irrespective of the size of the online business, a situation of a disaster would bring the entire operation of the system to a state of halt. The business should be able to recover itself as soon as possible in order to provide the continuity of the services to the clients and the consumers of the business. Downtime is one of the largest expenses of IT, which could be faced by any kind of business. With the help of the a proper DRP, a company or a business could save themselves from several kinds of risks that would also include out of the budget expenses, loss of the reputation of the company, loss of important data and hence would provide a negative impact on the customers and the clients (Yang, Yuan and Huang 2015).
Customer-Centric Strategy for Agriculture Organizations
Conclusion and Recommendations
Based on the above report, it can be concluded that the advent of digital technology could play a vital role in the field of agriculture. The report discusses about the various forms of systems for the collection of the data and the various forms of systems for the storage. These data storage systems are much vital for the collection of the vital information that are in relation with the agricultural sector. The collective use of big data tools and the other tools of cloud computing have helped in the storage of the data systems within the agricultural field. Although the use of big data within the smart farming techniques is at the primary stage of their development, yet they have made a major amount of impact at the places where the technology is being used. Many of the global based issues such as the security and the safety of food are being addressed with the applications of big data. The report also discusses about the consumer centric product design, which described the fact that different organizations and businesses should put forward their consumers on the topmost priority. They should be listening to the complaints and the grievances of the consumers in order to decide about the best possible measures, which should be designed in order to solve the various issues. Based on the consumer based actions, a proper system of recommendation have to be designed that would be able to tackle the several issues related to the agricultural sector. These would be helpful in increasing the yield and better production of crops in the future.
The use of big data has played a major role within the scope of the organization. Many of the global issues that are related to the security and the safety of food, sustainability could be addressed with the applications of Big Data. The issues that are faced in the agricultural sector could be solved within the scope of the big data applications (Lokers et al. 2016). The use of the technology of Internet of Things (IoT) could also bring about a major change within the industry. The agricultural sector is mostly referred to as the form of an industry that would be able to gain much amount of profits with the coupling of the IoT framework. The IoT technology would be helpful in providing the ability to collect the objective based information in an automatic way. These information could be in relation with the status of the conditions of the soil, crops, water and animals. The development of the IoT framework, which would help in connecting every kind of devices and objects within the farming environment and the chain of supply would also help in producing many of the new kind of data that are accessible in real time environment (Dlodlo and Kalezhi 2015). The transactions and operations are also regarded as one of the sources of process mediated data. Different kinds of sensors and robots would also help in producing non-traditional data. With regards to the traditional methods of the manual collection of data, it has been seen that digital based technology could provide better insights for the higher production and yield within the agricultural sector.
Shift towards Smart Farming
References
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