... Creative Destruction ( Johnson and Lewis, 1995) is the only solution to achieve this big hairy audacious goal of doubling the crop yield ..i.e.. stop the old or traditional habit (100 % dependency on manpower) in farming, by using ICT ( Information and communication technologies) Application of technology in farming was used for 5 years from 1983 and published in 1989 [1] This has resulted in generating more revenues ( enhanced crop yield) and reducing the expenses ( drop in usage of fertilizer ) [93], Nano technology [92], LIDAR [82], Swam farm robot [91], Nanostructured sensors [71], Cyber physical systems [72] [75] [77], Mobile agriculture robot swarms [72], Block chain [74], web of things [75],Next generation internet [76], Digital Twin [87] [90], Reinforcement learning [88], Cybernetics [89] [90], Edge Computing [98] Tey&Brindal (2012) has identified 34 factors grouped under conditions related to 1) socioeconomic factors (age, education, gender, credit, risk aversion, credit source, experience in agriculture, experience in use of technologies for agriculture etc), 2) agro ecological factors ( farm size, soil quality, productivity etc..), 3) institutional factors ( distance from market , fertilizer shop, region etc..), 4) information sources (access to information, consultants , access to technical companies, agencies etc..), 5) perception of the farmer (profits through technology vs capital intensity of technology), 6) behavioral factors (visibility of results, intention, perceived relative advantage etc..) and 7) technological factors ( computer knowledge, farm irrigation structure etc..) ...
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UN Report on “ World Population Prospects “ dated 17th Dec 2019 has projected that world population to reach 9.7 billion by 2050. India is one among the 9 countries that will make up for greater than 50 % of the projected growth. UN has predicted that world might face food supply challenge due to mismatch between growth in population and crop yield . Root Cause Analysis ( RCA) suggest that quantity and quality of the crop yield has notincreased to the desired level. To handle VUCA world (Volatile, Uncertain, Complex and Ambiguous ) and address the challenge, traditional methods are no longer sufficient. Solution given by Bill George of Harvard Business School is VUCA 2.0 ( Vision, Understanding Courage and Adaptability ). Doubling the crop yield up to year 2050, will prevent starvation and will help us to move towards UNSD -2030 Agenda. Innovation is the key to achieve this Big Hairy Audacious Goal (B -HAG), in the age of disruption , agriculture 4.0 and agriculture 5.0. Many countries have started using ICT (Internet of Things (IoT), Machine learning (ML), Deep learning (DL), Unmanned ground vehicles (UGV), Unmanned aerial vehicles (UAV)) at different stages of farming and enjoyed the benefits But, usage of ICT in farming, is yet to gain popularity in India. Barriers in adoption of technology innovation by Indian farmers includes high investment and lack of knowledge . The paper recommends adoption of Blue Ocean Strategy (BoS), Creative Destruction (CD) and suggest a framework using Trans Disciplinary Research (TDR)
Digital transformation is pushing all market sectors to level up their digital capabilities to better serve customers and improve the user experience. The European Commission launched in 2016 the Next Generation Internet (NGI) initiative as part of the DSM strategy. NGI includes a number of different – but always interrelated – emerging technologies in the following focus areas: artificial intelligence and autonomous machines, blockchains and distributed ledgers, big data, Internet of Things, 5G, cybersecurity and privacy technologies, cloud and edge computing, and open data. As for cooperation in the field of Information and Communications Technology, Europe and the United States should seek a joint framework to expand efforts in new emerging technologies, while preserving common principles around a comprehensive EU–US digital economy dialogue. The NGI Initiative is an important opportunity to radically rethink the way the Internet works today, and more human‐focused narratives are needed more than ever.
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This paper focuses on the the emerging transmission technologies dedicated to IoT networks. We first analyze the classical cellular network technologies when taking into account the IoT requirements, and point out the need of dedicated technologies for IoT. Then, we present the PHY and MAC layers of the technologies that are already deployed, or likely to be deployed: UNB by SigFox, CSS by LoRa T M , Weighless, and RPMA by Ingenu. We then compare their performances to highlight their pros and cons. Finally, we discuss on the open research challenges that still need to be addressed.
Long-range radio can connect sensors/IoT devices without complex and costly deployment of relay nodes. However, this flexibility comes with stricter legal regulations such asmaximum radio activity time per 1-hour period. Under such constraints it is difficult to provide service guarantees, which is quite paradoxical when devices are deployed for surveillance systems. The approach we propose allows devices to go "exceptionally" beyond the activity time limitation by borrowing time from other devices. The mechanism is not intended to be used on a regular basis, where a device is commissioned to always report data at a rate that makes it consuming more than the allowed duty-cycle limitation, but to offer a "last chance" solution for providing better surveillance service guarantees while globally satisfying duty-cycle regulations. The proposition has been implemented on our long-range image sensor platform, and preliminary experiments show that it can maintain the system's consistency and keep the number of control messages small while being capable of handling sleep-wakeup behavior and dynamic insertion of new devices. Although initially targeted for image sensors, the proposition can also be deployed to increase the quality of service of traditional sensors by guaranteeing that important messages can be sent despite the duty-cycle regulation limit.
LoRa modulation basics. rev.2-05
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