You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Multimedia Internet of Things: A Comprehensive Survey 
Chapter Title:  3) SMART AGRICULTURE 
1. Abstract of Cited Paper (BIB001):  There has been much research and various attempts to apply new IoT technology to agricultural areas. However, IoT for the agriculture should be considered differently against the same areas such as industrial, logistics. This paper presents the IoT-based agricultural production system for stabilizing supply and demand of agricultural products while developing the environment sensors and prediction system for the growth and production amount of crops by gathering its environmental information. Currently, the demand by consumption of agricultural products could be predicted quantitatively, however, the variation of harvest and production by the change of farm's cultivated area, weather change, disease and insect damage etc. could not be predicted, so that the supply and demand of agricultural products has not been controlled properly. To overcome it, this paper designed the IoT-based monitoring system to analyze crop environment, and the method to improve the efficiency of decision making by analyzing harvest statistics. Therefore, this paper developed the decision support system to forecast agricultural production using IoT sensors. This system was also a unified system that supports the processes sowing seeds through selling agricultural products to consumers. 3 Corresponding author The IoT-based agricultural production system through correlation analysis between the crop statistical information and agricultural environment information has enhanced the ability of farmers, researchers, and government officials to analyze current conditions and predict future harvest. Additionally, agricultural products quality can be improved because farmers observe whole cycle from seeding to selling using this IoT-based decision support system. 
2. Abstract of Cited Paper (BIB002):  Wireless sensor Network based automated irrigation system for optimize water use for agricultural purpose. The system consists of distributed wireless sensor network of soli-moisture, and temperature sensors placed in the crop field. To handle the sensor information Zigbee protocol used and control the water quantity programming using an algorithm with threshold values of the sensors to a microcontroller for irrigation system. The system has powered by solar panel and Cellular-internet interface for data inspection. A wireless camera is fixed in crop field to monitor the disease area using image processing technique. The system is low cost and energy autonomy useful in water limited geographically isolated areas. 
3. Abstract of Cited Paper (BIB003):  In this paper, we propose a cooking recipe recommendation system which runs on a consumer smartphone as an interactive mobile application. The proposed system employs real-time visual object recognition of food ingredients, and recommends cooking recipes related to the recognized food ingredients. Because of visual recognition, by only pointing a built-in camera on a smartphone to food ingredients, a user can get to know a related cooking recipes instantly. The objective of the proposed system is to assist people who cook to decide a cooking recipe at grocery stores or at a kitchen. In the current implementation, the system can recognize 30 kinds of food ingredient in 0.15 seconds, and it has achieved the 83.93% recognition rate within the top six candidates. By the user study, we confirmed the effectiveness of the proposed system. 
4. Abstract of Cited Paper (BIB004):  The Internet of things (IOT) is remodeling the agriculture enabling the farmers with the wide range of techniques such as precision and sustainable agriculture to face challenges in the field. IOT technology helps in collecting information about conditions like weather, moisture, temperature and fertility of soil, Crop online monitoring enables detection of weed, level of water, pest detection, animal intrusion in to the field, crop growth, agriculture. IOT leverages farmers to get connected to his farm from anywhere and anytime. Wireless sensor networks are used for monitoring the farm conditions and micro controllers are used to control and automate the farm processes. To view remotely the conditions in the form of image and video, wireless cameras have been used. A smart phone empowers farmer to keep updated with the ongoing conditions of his agricultural land using IOT at any time and any part of the world. IOT technology can reduce the cost and enhance the productivity of traditional farming.

Literature Review:
Agriculture is another important industrial sector. Researchers are trying to revolutionize the agriculture sector to increase its productivity by incorporating M-IoT (See Fig. 7b ). Nisha and Megala BIB003 present automatic irrigation and an infected area monitoring system using a wireless camera in the crop field to aid farmers. Zigbee transceiver is deployed to incorporate low power Zigbee over IEEE 802.15.4 protocol for communication and managing sensors data. K-means clustering machine algorithm is used for the detection of disease, color determination, and pest detection. Agricultural production framework to monitor and predicts the future harvest of crops to maintain balance in supply and demand is proposed in BIB002 . The software-based visual general user interface is implemented, and live streaming of the field crop is obtained by deploying a wireless camera. Dynamic data analysis for crop growth management system using IoT is proposed in BIB001 . The dynamic system equips the farmer with the historically analyzed data on a smartphone while moving in the field by communicating with the nearest deployed sensor node. An efficient low power MAC-based WSN working in a dynamic duty cycle scheme is presented in work to resolve the congestion condition. The system is evaluated in the context of packet delivery ratio, end-to-end delay, and duty cycles. Authors in BIB005 present a detailed study of various IoT agricultural crop monitoring systems. Android-based food recognition application to automatically recommend a cooking recipe is presented in BIB004 . The proposed work employs Speeded-Up Robust Features (SURF) with the Hessian detector to extract 144 64-dimension features, Bag-of-Features (BoF) for feature representation technique and SVM as a classifier. The proposed scheme gives 84% of the recognition rate. Witjaksono et al. in  exploits IoT based application for images recognition to determine the freshness of the food. The application also discriminates halal meat from non-halal meat for Muslims.