A Comparative study on Internet Of Things (IoT) and its applications in Smart Agriculture

Srilakshmi, A.; Rakkini, M. J. Jeyasheela; Sekar, K. R.; Manikandan, R.

doi:10.5530/pj.2018.2.46

Cited by 32 publications

(6 citation statements)

References 7 publications

(8 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The second industry sector that is most influenced by IoT is the agricultural sector where the IoT has recently been applied in agrarian countries, as stated by (Mushtaq, 2018; Srilakshmi et al., 2018) this is driven because IoT contributes significantly to socio-economic growth, Increasing Productivity, Reducing Costs and Optimizing time for farmers in particular, and also this sector produces a basic need that has a great effect on a country in general where its development is strongly influenced by how is the government's strategy (Saragih et al., 2018).…”

Section: Resultsmentioning

confidence: 99%

“…Agri-crisis occurs due to rain and poor climatic conditions, so farmers suffer from severe scarcity and have difficulty recovering from drought. IoT is a technology that serves as a solution to this problem (Srilakshmi et al., 2018). To do air quality tracking carried out only at the macro level, detailed hyper-local data is difficult to obtain because of the lack of sensors that collect information (Meinert et al., 2018).…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Knowledge growth and development: internet of things (IoT) research, 2006–2018

Dachyar

Zagloel

Saragih

2019

Heliyon

View full text Add to dashboard Cite

The term "Internet of Things" first appeared in publication paper since 2006, describing the paradigm of evolution concept that brought about by the presence of internet technology (Vermesan and Friess, 2015) which is very important in contemporary circumstances. This study conducted an in-depth analysis of the research material written on 26420 papers which focused on the published Internet of Things (IoT) research, starting from the firstly year IoT keyword appeared in 2006 until 2018. The selected paper is a combination of various disciplines and publications which are all indexed by Scopus wherein the article discusses IoT. IoT articles are classified using key attributes in sequence: the methodology used, general knowledge and applied concepts, and various general exploration topics. By using the Scientometrics method, this method will group the overall terms that appear frequently from the Scopus paper database according to keywords, titles, and abstracts. The resulting data is then studied to understand and distinguish trends that occur in the time span along with the general characteristics of the paper, in the mathematics visual scheme. All various issues that are considered in the paper's methodology selection, their studied and services innovations, and continuing discoveries on the characteristics, concepts, and processes applied to IoT success. Although it only involves scopus indexed paper, this study found a remarkable increase in the number of articles on IoT in each category of the paper. This study also reveals the direction of the regular discipline of knowledge. The use of the Scientometrics method makes the analysis able to focus on the movement of characteristics and IoT themes to researcher's direction that has not found at this time, as a comprehensive guide to further research and industry strategy that is more directed on concepts that support the 4th industrial revolution.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Knowledge growth and development: internet of things (IoT) research, 2006–2018

Dachyar

Zagloel

Saragih

2019

Heliyon

View full text Add to dashboard Cite

show abstract

“…In the congestion scenario 𝐵𝐹(𝑥) ≥ 𝐵𝐹 𝑡ℎ , 𝐵𝐹(𝑥) exhibits the effective impact over the 𝐸𝑇𝑋(𝑥, 𝑦) and 𝑆(𝑥) compared with 𝐵𝐹(𝑥). Concerning received feedback 𝐻(𝑥) with the updated node value of 𝑄 𝑡𝑎𝑏𝑙𝑒 (𝑥) as stated in equation (1). Based on the greedy selection policy neighboring nodes are the value of parent are computed with minimal Qvalue of neighbor nodes.…”

Section: Trickle-timer Estimation With Developed Genetic Q-learningmentioning

confidence: 99%

“…Internet of Things (IoT) is a network that connects some significant number of objects where an object is characterized as (1) physical or virtual, (2) decisions and functioning are independent, (3) capable of communicating with other devices, (4) operates interactively since integrated with heterogeneous devices, and (5) flexibly interacts with objects for any type of service anytime and anywhere [1]. However, recently, from a technical point of view, IoT fuses several networking technologies like Radio Frequency Identification (RFID), Wireless Sensor Networks (WSN), Vehicular Ad hoc Networks (VANET), Smart ad hoc networks, WIrelessFIdelity Networks (WIFI), Wireless Personal Area Network (WPAN), and many others; thus IoT is a vast heterogeneous network [2].…”

Section: Introductionmentioning

confidence: 99%

Untitled

2022

IJNSA

View full text Add to dashboard Cite

Internet of Things (IoT) offers reliable and seamless communication for the heterogeneous dynamic lowpower and lossy network (LLNs). To perform effective routing in IoT communication, LLN Routing Protocol (RPL) is developed for the tiny nodes to establish connection by using deflaut objective functions: OF0, MRHOF, for which resources are constraints like battery power, computation capacity, memory communication link impacts on varying traffic scenarios in terms of QoS metrics like packet delivery ratio, delay, secure communication channel. At present, conventional Internet of Things (IoT) are having secure communication channels issue for transmission of data between nodes. To withstand those issues, it is necessary to balance resource constraints of nodes in the network. In this paper, we developed a security algorithm for IoT networks with RPL routing. Initially, the constructed network in corporates optimizationbased deep learning (reinforcement learning) for route establishment in IoT. Upon the establishment of the route, the ClonQlearn based security algorithm is implemented for improving security which is based onaECC scheme for encryption and decryption of data. The proposed security technique incorporates reinforcement learning-based ClonQlearnintegrated with ECC (ClonQlearn+ECC) for random key generation. The proposed ClonQlearn+ECCexhibits secure data transmission with improved network performance when compared with the earlier works in simulation. The performance of network expressed that the proposed ClonQlearn+ECC increased the PDR of approximately 8% -10%, throughput of 7% -13%, end-to-end delay of 5% -10% and power consumption variation of 3% -7%.

show abstract

“…e smart irrigation decision support system (SIDSS) is a novel technique that uses field deployed sensors to detect soil characteristics, weather and climate conditions, and crop conditions for irrigation [13]. In this regard, Kamienski et al proposed an IoTbased smart water management platform (SWAMP) intelligent irrigation system [1,14].…”

Section: Introductionmentioning

confidence: 99%

EEWMP: An IoT-Based Energy-Efficient Water Management Platform for Smart Irrigation

Ullah

Abbas

Ullah

et al. 2021

Scientific Programming

View full text Add to dashboard Cite

Precision agriculture is now essential in today’s world, especially for countries with limited water resources, fertile land, and enormous population. Smart irrigation systems can help countries efficiently utilize fresh water and use the excess water for barren lands. Smart water management platform (SWAMP) is an IoT-based smart irrigation project designed for efficient freshwater utilization in agriculture. The primary aim of SWAMP is to auto manage water reserves, distribution, and consumption of various levels, avoid over-irrigation and under-irrigation problems, and auto manage time to maximize production. This research proposed an energy-efficient water management platform (EEWMP), an improved version of SWAMP. EEWMP is an IoT-based smart irrigation system that uses field-deployed sensors, sinks, fusion centres, and open-source clouds. Both models’ performance is evaluated in energy consumption, network stability period, packet sent to destination, and packet delivery ratio. The experimental results show that EEWMP consumes 30% less energy and increases network stability twice than SWAMP. EEWMP can be used in different irrigation models such as drip irrigation, sprinkler irrigation, surface irrigation, and lateral move irrigation with subtle alterations. Moreover, it can also be used in small farms of third-world countries with their existing communication infrastructures such as 2G or 3G.

show abstract

A Comparative study on Internet Of Things (IoT) and its applications in Smart Agriculture

Cited by 32 publications

References 7 publications

Knowledge growth and development: internet of things (IoT) research, 2006–2018

Knowledge growth and development: internet of things (IoT) research, 2006–2018

Untitled

EEWMP: An IoT-Based Energy-Efficient Water Management Platform for Smart Irrigation

Contact Info

Product

Resources

About