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A field experiment was conducted during Kharif 2018 at College Farm, College of Agriculture, PJTSAU to evaluate the effect of various sources of zinc and iron on grain yield, nutrient uptake and grain quality parameters of finger millet. The experiment was laid out in a randomized block design with 14 treatments and replicated thrice.The results revealed that application of different Zinc and iron sources at different rates significantly influenced the grain yield, nutrient (N, P and K) uptake and grain quality parameters (protein and calcium content) of finger millet. Highest grain yield (3653 kg ha-1), protein (11.25%) and calcium content (2.33%) in grain were obtained in the treatment receiving RDF + foliar application of FeSO4 @ 0.5% twice at 30 and 60 DAS which was on par with treatment receiving RDF + foliar application of Fe-humate twice at 30 and 60 DAS (3612 kg ha-1, 10.90% and 2.0%) and the lowest grain yield (1995 kg ha-1), (6.25%) and calcium content (1.10%) were recorded with application of RDF alone. The nutrient uptake (N, P, K and Fe) at all the crop growth stages was significantly higher with the treatment receiving RDF (60:40:30 kg N,P2O5 and K2O kg ha-1) + foliar application of FeSO4 @ 0.5% twice at 30 and 60 DAS which was on par with treatment receiving RDF+ foliar application of Fe-humate twice at 30 and 60 DAS. Highest iron uptake was recorded in treatment receiving RDF+foliar application of FeSO4 @ 0.5% twice at 30 and 60 DAS which was on par with T8, T14 treatments.The highest nutrient uptake of Zinc was obtained in treatment receiving RDF + Zn Humate foliar spray @ 0.25% twice at 30 and 60 days after sowing which was on par with treatment receiving RDF + Zn Humate soil  application. Contrary to the grain yield, nutrient uptake, protein and calcium content there were no significant differences between treatments with respect to Zn, Fe and carbohydrate content in grain.

In a wireless sensor network, information processing, and information acquisition, localization technology is the key to making it practically possible application. Approximate Point-in-Triangulation (APIT) is the most widely used localization estimation which has high accuracy in localizing the nodes and ease of deployment of nodes in the real-time environment. Though it has numerous key advantages, some of the drawbacks which make it a little setback in preference are the unevenness in the distribution of nodes. Tracking is more appropriate for mobile sensor nodes than tracking is for static sensor nodes. The two main types of localization algorithms are range-based and range-free techniques. In an indoor setting, the projected range (distance) between an anchor and an unknown node is very inaccurate. By utilizing a large number of already existing access points (APs) in the range-free localization approach, this issue can be overcome to a great extent. The utilization of multisensor data, such as magnetic, inertial, compass, gyroscope, ultrasonic, infrared, visual, and/or odometer, is stressed in recent research to further increase localization accuracy. The tracking system also makes location predictions for the future based on historical location data. To overcome this issue, the proposed localization algorithm of APIT with Bat-SA proves its efficiency. Due to its low localization error, the traditional Bat method is more accurate than APIT. The proposed Bat using the SA algorithm is found to perform better than the traditional APIT algorithm in terms of convergence of computing rate and success rate. In order to mimic the suggested APIT method, it is paired with the Bat-SA localization technique. Simulation evaluation proves the performance efficiency of the proposed algorithm. The performance metrics parameters are latency, node distribution map, positioning error map, and neighbor relationship diagram which are used to evaluate the proposed method.